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1041e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 \u0438 \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u0432\u0438\u0434\u044b \u0437\u0430\u0434\u0430\u0447.","sidebar":"Machine-learning"},"Machine-learning/Base-concepts/Weighted-account":{"id":"Machine-learning/Base-concepts/Weighted-account","title":"\u0412\u0437\u0432\u0435\u0448\u0435\u043d\u043d\u044b\u0439 \u0443\u0447\u0451\u0442 \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u0439","description":"\u0423\u0447\u0451\u0442 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043e\u0431\u0443\u0447\u0430\u044e\u0449\u0435\u0439 \u0432\u044b\u0431\u043e\u0440\u043a\u0438 \u0441 \u0440\u0430\u0437\u043d\u044b\u043c\u0438 \u0432\u0435\u0441\u0430\u043c\u0438 - \u0444\u043e\u0440\u043c\u0443\u043b\u0430, \u043c\u043e\u0442\u0438\u0432\u0430\u0446\u0438\u044f \u043f\u0440\u0438\u043c\u0435\u0440\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Bias-variance/Bias-variance-decomposition":{"id":"Machine-learning/Bias-variance/Bias-variance-decomposition","title":"\u0420\u0430\u0437\u043b\u043e\u0436\u0435\u043d\u0438\u0435 \u043d\u0430 \u0441\u043c\u0435\u0449\u0435\u043d\u0438\u0435 \u0438 \u0440\u0430\u0437\u0431\u0440\u043e\u0441","description":"\u0420\u0430\u0437\u043b\u043e\u0436\u0435\u043d\u0438\u0435 \u043d\u0430 \u0441\u043c\u0435\u0449\u0435\u043d\u0438\u0435 \u0438 \u0440\u0430\u0437\u0431\u0440\u043e\u0441 (bias-variance decomposition) - \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f, \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u044b \u0440\u0430\u0437\u043b\u043e\u0436\u0435\u043d\u0438\u044f \u0434\u043b\u044f \u043f\u0435\u0440\u0435\u043e\u0431\u0443\u0447\u0435\u043d\u043d\u044b\u0445 (overfitted) \u0438 \u043d\u0435\u0434\u043e\u043e\u0431\u0443\u0447\u0435\u043d\u043d\u044b\u0445 (underfitted) \u043c\u043e\u0434\u0435\u043b\u0435\u0439.","sidebar":"Machine-learning"},"Machine-learning/Bias-variance/Bias-variance-decomposition-proof":{"id":"Machine-learning/Bias-variance/Bias-variance-decomposition-proof","title":"\u0414\u043e\u043a\u0430\u0437\u0430\u0442\u0435\u043b\u044c\u0441\u0442\u0432\u043e \u0440\u0430\u0437\u043b\u043e\u0436\u0435\u043d\u0438\u044f","description":"\u0414\u043e\u043a\u0430\u0437\u0430\u0442\u0435\u043b\u044c\u043d\u0441\u0442\u0432\u043e \u0440\u0430\u0437\u043b\u043e\u0436\u0435\u043d\u0438\u044f \u043d\u0430 \u0441\u043c\u0435\u0449\u0435\u043d\u0438\u0435 \u0438 \u0440\u0430\u0437\u0431\u0440\u043e\u0441 (bias-variance decomposition).","sidebar":"Machine-learning"},"Machine-learning/Bias-variance/Literature":{"id":"Machine-learning/Bias-variance/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u043c\u0435\u0442\u043e\u0434\u0430\u043c \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Bias-variance/Model-complexity":{"id":"Machine-learning/Bias-variance/Model-complexity","title":"\u0421\u043b\u043e\u0436\u043d\u043e\u0441\u0442\u044c \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u044e\u0449\u0438\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439","description":"\u041f\u0435\u0440\u0435\u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 (overfitting) \u0438 \u043d\u0435\u0434\u043e\u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 (underfitting) \u0432 \u043c\u043e\u0434\u0435\u043b\u044f\u0445 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u0412\u0430\u0436\u043d\u043e\u0441\u0442\u044c \u043f\u043e\u0434\u0431\u043e\u0440\u0430 \u0441\u043b\u043e\u0436\u043d\u043e\u0441\u0442\u0438 (\u0432\u044b\u0440\u0430\u0437\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0439 \u0441\u043f\u043e\u0441\u043e\u0431\u043d\u043e\u0441\u0442\u0438) \u043c\u043e\u0434\u0435\u043b\u0438.","sidebar":"Machine-learning"},"Machine-learning/book-title":{"id":"Machine-learning/book-title","title":"\u041e\u043d\u043b\u0430\u0439\u043d-\u0443\u0447\u0435\u0431\u043d\u0438\u043a \u043f\u043e \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c\u0443 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044e (machine learning).","description":"\u041e\u043d\u043b\u0430\u0439\u043d-\u0443\u0447\u0435\u0431\u043d\u0438\u043a \u043f\u043e \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c\u0443 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044e (machine learning) \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u043a\u0443\u0440\u0441\u0430 \u043d\u0430 \u0412\u041c\u041a \u041c\u0413\u0423.","sidebar":"Machine-learning"}
1,"Machine-learning/Boosting/AdaBoost":{"id":"Machine-learning/Boosting/AdaBoost","title":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c AdaBoost","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c AdaBoost, \u0435\u0433\u043e \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u043f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u0438\u044f, \u0438\u043d\u0442\u0443\u0438\u0446\u0438\u044f \u0438 \u043c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0432\u044b\u0432\u043e\u0434. \u0418\u0434\u0435\u044f \u043e\u0431\u043e\u0431\u0449\u0435\u043d\u0438\u044f \u043c\u0435\u0442\u043e\u0434\u0430.","sidebar":"Machine-learning"},"Machine-learning/Boosting/Boosting-general":{"id":"Machine-learning/Boosting/Boosting-general","title":"\u0411\u0443\u0441\u0442\u0438\u043d\u0433","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430 - 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\u0441\u0442\u044d\u043a\u0438\u043d\u0433\u043e\u043c \u0438 \u0434\u0440\u0443\u0433\u0438\u043c\u0438 \u043c\u0435\u0442\u043e\u0434\u0430\u043c\u0438 \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u0435\u0439 \u043c\u043e\u0434\u0435\u043b\u0435\u0439.","sidebar":"Machine-learning"},"Machine-learning/Boosting/GB-accuracy":{"id":"Machine-learning/Boosting/GB-accuracy","title":"\u0422\u043e\u0447\u043d\u043e\u0441\u0442\u044c \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430","description":"\u0410\u043d\u0430\u043b\u0438\u0437 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430. \u0421\u043b\u0443\u0447\u0430\u0438, \u043a\u043e\u0433\u0434\u0430 \u0442\u043e\u0447\u043d\u0435\u0435 \u0440\u0430\u0431\u043e\u0442\u0430\u044e\u0442 \u043c\u0435\u0442\u043e\u0434 K \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0441\u043e\u0441\u0435\u0434\u0435\u0439 \u0438 \u043b\u0438\u043d\u0435\u0439\u043d\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438. \u0412\u0430\u0436\u043d\u043e\u0441\u0442\u044c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0434\u043b\u044f \u043f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u044f \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438.","sidebar":"Machine-learning"},"Machine-learning/Boosting/GB-algorithm":{"id":"Machine-learning/Boosting/GB-algorithm","title":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430","description":"\u041f\u043e\u0448\u0430\u0433\u043e\u0432\u044b\u0439 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c 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\u0438\u043d\u0442\u0443\u0438\u0446\u0438\u044f \u043c\u0435\u0442\u043e\u0434\u0430, \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u0438 \u043f\u0440\u0438\u043c\u0435\u0440 \u0435\u0433\u043e \u0440\u0430\u0431\u043e\u0442\u044b \u0432 \u0441\u043b\u0443\u0447\u0430\u0435 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0438 \u0431\u0438\u043d\u0430\u0440\u043d\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438. \u
10420\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u0438\u0435 \u043d\u0430 \u043c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u0443\u044e \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u044e.","sidebar":"Machine-learning"},"Machine-learning/Boosting/GB-illustration":{"id":"Machine-learning/Boosting/GB-illustration","title":"\u0418\u043b\u043b\u044e\u0441\u0442\u0440\u0430\u0446\u0438\u044f \u0440\u0430\u0431\u043e\u0442\u044b \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430 \u043f\u043e \u0448\u0430\u0433\u0430\u043c","description":"\u0412\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0440\u0430\u0431\u043e\u0442\u044b \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430 \u043f\u043e \u0448\u0430\u0433\u0430\u043c. \u0410\u043d\u0430\u043b\u0438\u0437 \u0438\u0437\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u043e\u0448\u0438\u0431\u043e\u043a \u0432 \u0437\u0430\u0432\u0438\u0441\u0438\u043c\u043e\u0441\u0442\u0438 \u043e\u0442 \u0448\u0430\u0433\u0430.","sidebar":"Machine-learning"},"Machine-learning/Boosting/GB-implementations":{"id":"Machine-learning/Boosting/GB-implementations","title":"\u041f\u043e\u043f\u0443\u043b\u044f\u0440\u043d\u044b\u0435 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438","description":"\u041f\u0440\u043e\u0434\u0432\u0438\u043d\u0443\u0442\u044b\u0435 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430 - xgBoost, LightGBM, CatBoost. \u041e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u0438\u0434\u0435\u0438 \u0443\u043b\u0443\u0447\u0448\u0435\u043d\u0438\u0439.","sidebar":"Machine-learning"},"Machine-learning/Boosting/GB-improvements":{"id":"Machine-learning/Boosting/GB-improvements","title":"\u0423\u043b\u0443\u0447\u0448\u0435\u043d\u0438\u044f \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u043f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u044f \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430 \u0437\u0430 \u0441\u0447\u0451\u0442 \u0441\u0436\u0430\u0442\u0438\u044f (shrinkage) \u0438 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0431\u0430\u0437\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u044f\u0445 \u043d\u0430 \u043f\u043e\u0434\u043c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u0430\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u0438 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 (subsampling). \u041c\u043e\u0442\u0438\u0432\u0430\u0446\u0438\u044f \u0443\u043b\u0443\u0447\u0448\u0435\u043d\u0438\u0439 \u0438 \u043f\u0440\u0438\u043c\u0435\u0440\u044b \u0440\u0430\u0431\u043e\u0442\u044b.","sidebar":"Machine-learning"},"Machine-learning/Boosting/GB-second-order":{"id":"Machine-learning/Boosting/GB-second-order","title":"\u0413\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u044b\u0439 \u0431\u0443\u0441\u0442\u0438\u043d\u0433 \u0432\u0442\u043e\u0440\u043e\u0433\u043e \u043f\u043e\u0440\u044f\u0434\u043a\u0430","description":"\u0413\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u044b\u0439 \u0431\u0443\u0441\u0442\u0438\u043d\u0433 \u0432\u0442\u043e\u0440\u043e\u0433\u043e \u043f\u043e\u0440\u044f\u0434\u043a\u0430 - \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u0439 \u0431\u0430\u0437\u043e\u0432\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0430 \u043f\u0440\u0438 \u043a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u043e\u043c \u043f\u0440\u0438\u0431\u043b\u0438\u0436\u0435\u043d\u0438\u0438 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043f\u043e\u0442\u0435\u0440\u044c.","sidebar":"Machine-learning"},"Machine-learning/Boosting/Literature":{"id":"Machine-learning/Boosting/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u043c\u0435\u0442\u043e\u0434\u0430\u043c \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Boosting/Questions":{"id":"Machine-learning/Boosting/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u043c\u0443 \u0431\u0443\u0441\u0442\u0438\u043d\u0433\u0443.","sidebar":"Machine-learning"},"Machine-learning/Boosting/xgBoost-algorithm":{"id":"Machine-learning/Boosting/xgBoost-algorithm","title":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c XGBoost","description":"\u041c\u043e\u0434\u0435\u043b\u044c xgBoost: \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c, \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435, \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u0438 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438.","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/AUC":{"id":"Machine-learning/Classifier-evaluation/AUC","title":"\u042d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u043e\u0435 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 AUC","description":"\u042d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u043e\u0435 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 AUC (area under curve) \u043a\u0430\u043a \u0434\u043e\u043b\u0438 \u0432\u0435\u0440\u043d\u043e \u0443\u043f\u043e\u0440\u044f\u0434\u043e\u0447\u0435\u043d\u043d\u044b\u0445 \u043f\u0430\u0440 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432. \u0414\u043e\u043a\u0430\u0437\u0430\u0442\u0435\u043b\u044c\u0441\u0442\u0432\u043e \u044d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u043e\u0441\u0442\u0438. \u
10421\u043f\u043e\u0441\u043e\u0431 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 AUC \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u044b\u043c\u0438 \u043c\u0435\u0442\u043e\u0434\u0430\u043c\u0438 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 \u043d\u0430\u043f\u0440\u044f\u043c\u0443\u044e.","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/Literature":{"id":"Machine-learning/Classifier-evaluation/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u043c\u0435\u0442\u043e\u0434\u0430\u043c \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/Multiclass-generalization-of-binary-measures":{"id":"Machine-learning/Classifier-evaluation/Multiclass-generalization-of-binary-measures","title":"\u041e\u0431\u043e\u0431\u0449\u0435\u043d\u0438\u0435 \u0431\u0438\u043d\u0430\u0440\u043d\u044b\u0445 \u043c\u0435\u0440 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043d\u0430 \u043c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u044b\u0439 \u0441\u043b\u0443\u0447\u0430\u0439","description":"\u0420\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u0438\u0435 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u0438 \u0438 \u043f\u043e\u043b\u043d\u043e\u0442\u044b \u0434\u043b\u044f \u043e\u0446\u0435\u043d\u043a\u0438 \u043c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u044b\u0445 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432. \u041c\u0438\u043a\u0440\u043e\u0443\u0441\u0440\u0435\u0434\u043d\u0435\u043d\u0438\u0435 \u0438 \u043c\u0430\u043a\u0440\u043e\u0443\u0441\u0440\u0435\u0434\u043d\u0435\u043d\u0438\u0435. \u041c\u0435\u0440\u0430 mean average precision (mAP).","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/Probability-calibration":{"id":"Machine-learning/Classifier-evaluation/Probability-calibration","title":"\u041a\u043e\u043d\u0442\u0440\u043e\u043b\u044c \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043f\u0440\u0435\u0434\u0441\u043a\u0430\u0437\u0430\u043d\u0438\u044f \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u043e\u0441\u0442\u0435\u0439","description":"\u041a\u0430\u043b\u0438\u0431\u0440\u043e\u0432\u043a\u0430 \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u043e\u0441\u0442\u0435\u0439 \u0438 \u043c\u0435\u0442\u043e\u0434\u044b \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u043e\u0441\u0442\u043d\u044b\u0445 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432. \u041c\u0435\u0440\u0430 \u0411\u0440\u0438\u0435\u0440\u0430 (Brier score).","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/Questions":{"id":"Machine-learning/Classifier-evaluation/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u043c\u0435\u0442\u043e\u0434\u0430\u043c \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/ROC-curve-AUC":{"id":"Machine-learning/Classifier-evaluation/ROC-curve-AUC","title":"ROC-\u043a\u0440\u0438\u0432\u0430\u044f","description":"\u041e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 ROC-\u043a\u0440\u0438\u0432\u043e\u0439 (ROC-curve). \u041f\u043b\u043e\u0449\u0430\u0434\u044c \u043f\u043e\u0434 ROC-\u043a\u0440\u0438\u0432\u043e\u0439 AUC (area under curve). \u041c\u0435\u0440\u044b true positive rate (TPR), false positive rate (FPR) \u0432 \u0431\u0438\u043d\u0430\u0440\u043d\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/ROC-curve-best-point":{"i
1d":"Machine-learning/Classifier-evaluation/ROC-curve-best-point","title":"\u041b\u0443\u0447\u0448\u0438\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0442\u043e\u0440 \u043d\u0430 ROC \u043a\u0440\u0438\u0432\u043e\u0439","description":"\u041d\u0430\u0445\u043e\u0436\u0434\u0435\u043d\u0438\u0435 \u043d\u0430\u0438\u043b\u0443\u0447\u0448\u0435\u0433\u043e \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0442\u043e\u0440\u0430 \u043d\u0430 ROC-\u043a\u0440\u0438\u0432\u043e\u0439.","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/Special-binary-label-quality-estimation":{"id":"Machine-learning/Classifier-evaluation/Special-binary-label-quality-estimation","title":"\u0421\u043f\u0435\u0446\u0438\u0430\u043b\u044c\u043d\u044b\u0435 \u043c\u0435\u0440\u044b \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u0434\u043b\u044f \u0431\u0438\u043d\u0430\u0440\u043d\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438","description":"\u0421\u043f\u0435\u0446\u0438\u0430\u043b\u044c\u043d\u044b\u0435 \u043c\u0435\u0440\u044b \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0432 \u0437\u0430\u0434\u0430\u0447\u0435 \u0431\u0438\u043d\u0430\u0440\u043d\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438, precision \u0438 recall, F-\u043c\u0435\u0440\u0430. \u0417\u0430\u0434\u0430\u0447\u0430 \u0440\u0430\u043d\u0436\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f. \u041c\u0435\u0440\u044b precision@K, recall@K, Average Precision.","sidebar":"Machine-learning"},"Machine-learning/Classifier-evaluation/Standard-multiclass-label-quality-estimation":{"id":"Machine-learning/Classifier-evaluation/Standard-multiclass-label-quality-estimation","title":"\u0411\u0430\u0437\u043e\u0432\u044b\u0435 \u043c\u0435\u0440\u044b \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438","description":"\u041e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u043c\u0435\u0440\u044b \u0434\u043b\u044f \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438. \u0422\u043e\u0447\u043d\u043e\u0441\u0442\u044c, \u0447\u0430\u0441\u0442\u043e\u0442\u0430 \u043e\u0448\u0438\u0431\u043e\u043a, \u043c\u0430\u0442\u0440\u0438\u0446\u0430 \u043e\u0448\u0438\u0431\u043e\u043a. \u0412\u0437\u0432\u0435\u0448\u0435\u043d\u043d\u044b\u0439 \u0443\u0447\u0451\u0442 \u043e\u0448\u0438\u0431\u043e\u043a \u0440\u0430\u0437\u043d\u044b\u0445 \u0442\u0438\u043f\u043e\u0432.","sidebar":"Machine-learning"},"Machine-learning/Clustering-evaluation/Clustering-evaluation":{"id":"Machine-learning/Clustering-evaluation/Clustering-evaluation","title":"\u041c\u0435\u0442\u043e\u0434\u044b \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438","description":"\u041e\u0446\u0435\u043d\u043a\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438","sidebar":"Machine-learning"},"Machine-learning/Clustering-evaluation/External-clustering-evaluation-measures":{"id":"Machine-learning/Clustering-evaluation/External-clustering-evaluation-measures","title":"\u0412\u043d\u0435\u0448\u043d\u0438\u0435 \u043c\u0435\u0440\u044b \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430","description":"\u0412\u043d\u0435\u0448\u043d\u0438\u0435 \u043c\u0435\u0440\u044b \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Clustering-evaluation/Internal-clustering-evaluation-measures":{"id":"Machine-learning/Clustering-evaluation/Internal-clustering-evaluation-measures","title":"\u0412\u043d\u0443\u0442\u0440\u0435\u043d\u043d\u0438\u0435 \u043c\u0435\u0440\u044b \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430","description":"\u0412\u043d\u0443\u0442\u0440\u0435\u043d\u043d\u0438\u0435 \u043c\u0435\u0440\u044b \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Clustering-evaluation/Literature":{"id":"Machine-learning/Clustering-evaluation/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430 \u043f\u043e \u043e\u0446\u0435\u043d\u043a\u0435 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Clustering/Clustring-Intro":{"id":"Machine-learning/Clustering/Clustring-Intro","title":"\u041a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u044f \u0434\u0430\u043d\u043d\u044b\u0445","description":"\u0417\u0430\u0434\u0430\u0447\u0430 \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438 \u0438 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438 \u0434\u0430\u043d\u043d\u044b\u0445.","sidebar":"Machine-learning"},"Machine-learning/Clustering/DBSCAN":{"id":"Machine-learning/Clustering/DBSCAN","title":"DBSCAN","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438 DBSCAN.","sidebar":"Machine-learning"},"Machine-learning/Clustering/K-means":{"id":"Machine-learning/Clustering/K-means","title":"\u041c\u0435\u0442\u043e\u0434 K-\u0441\u0440\u0435\u0434\u043d\u0438\u0445","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438 K-\u0441\u0440\u0435\u0434\u043d\u0438\u0445 \u0438 \u0435\u0433\u043e \u043c\u043e\u0434\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Clustering/K-representatives-variations":{"id":"Machine-learning/Clustering/K-representatives-variations","title":"\u0412\u0430\u0440\u0438\u0430\u0446\u0438\u0438 \u043c\u0435\u0442\u043e\u0434\u0430 K \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u0442\u0435\u043b\u0435\u0439","description":"\u0412\u0430\u0440\u0438\u0430\u0446\u0438\u0438 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0430 K-\u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u0442\u0435\u043b\u0435\u0439: K-medians, K-medoids, clustering with Mahalanobis distance.","sidebar":"Machine-learning"},"Machine-learning/Clustering/Representative-based-clustering":{"i
1d":"Machine-learning/Clustering/Representative-based-clustering","title":"\u041a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u044f K \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u0442\u0435\u043b\u044f\u043c\u0438","description":"\u041c\u0435\u0442\u043e\u0434 \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0438\u0437\u0430\u0446\u0438\u0438 K-\u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u0442\u0435\u043b\u0435\u0439 \u0432 \u043e\u0431\u0449\u0435\u043c \u0432\u0438\u0434\u0435 \u0438 \u0441\u043f\u043e\u0441\u043e\u0431\u044b \u0435\u0433\u043e \u0438\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438. \u041c\u0435\u0442\u043e\u0434 K-means++.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Counterfactual-explanations":{"id":"Machine-learning/Complex-models-interpretation/Counterfactual-explanations","title":"\u041a\u043e\u043d\u0442\u0440\u0444\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u044f","description":"\u0410\u043d\u0430\u043b\u0438\u0437 \u0438 \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u043c\u043e\u0434\u0435\u043b\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043a\u043e\u043d\u0442\u0440\u0444\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0439 (counterfactual explanations). \u041c\u0435\u0442\u043e\u0434 \u0440\u0430\u0441\u0447\u0451\u0442\u0430 \u0438 \u043f\u0440\u0438\u043c\u0435\u0440\u044b \u043a\u043e\u043d\u0442\u0440\u0444\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0439.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Error-analysis":{"id":"Machine-learning/Complex-models-interpretation/Error-analysis","title":"\u0410\u043d\u0430\u043b\u0438\u0437 \u043e\u0448\u0438\u0431\u043e\u043a \u043c\u043e\u0434\u0435\u043b\u0438","description":"\u0410\u043d\u0430\u043b\u0438\u0437 \u043e\u0448\u0438\u0431\u043e\u043a \u043c\u043e\u0434\u0435\u043b\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0433\u0440\u0430\u0444\u0438\u043a\u0430 \u0437\u0430\u0432\u0438\u0441\u0438\u043c\u043e\u0441\u0442\u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u043e\u0442 \u0440\u0435\u0430\u043b\u044c\u043d\u044b\u0445. \u041c\u0430\u0442\u0440\u0438\u0446\u0430 \u043e\u0448\u0438\u0431\u043e\u043a.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Feature-dependency":{"id":"Machine-learning/Complex-models-interpretation/Feature-dependency","title":"\u0417\u0430\u0432\u0438\u0441\u0438\u043c\u043e\u0441\u0442\u044c \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0430 \u043e\u0442 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432","description":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0437\u0430 \u0441\u0447\u0451\u0442 \u0430\u043d\u0430\u043b\u0438\u0437\u0430 \u0432\u043b\u0438\u044f\u043d\u0438\u044f \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u0430 \u043d\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437 \u043c\u043e\u0434\u0435\u043b\u0438. \u041c\u0435\u0442\u043e\u0434\u044b Partial Dependence Plot, Individual Conditional Expectation, Marginal Plot, Accumulated Local Effects. \u0418\u0445 \u0441\u0440\u0430\u0432\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u043f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430 \u0438 \u043d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043a\u0438. \u
1041f\u0440\u0438\u043c\u0435\u0440\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Fragments-impact":{"id":"Machine-learning/Complex-models-interpretation/Fragments-impact","title":"\u0412\u043b\u0438\u044f\u043d\u0438\u0435 \u0444\u0440\u0430\u0433\u043c\u0435\u043d\u0442\u043e\u0432 \u043d\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437","description":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0435\u0442\u043e\u0434\u043e\u043c \u043e\u0446\u0435\u043d\u043a\u0438 \u0432\u043b\u0438\u044f\u043d\u0438\u044f \u0444\u0440\u0430\u0433\u043c\u0435\u043d\u0442\u043e\u0432 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f \u043d\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437. \u0412\u044b\u0434\u0435\u043b\u0435\u043d\u0438\u0435 \u0444\u0440\u0430\u0433\u043c\u0435\u043d\u0442\u043e\u0432 \u043c\u0435\u0442\u043e\u0434\u043e\u043c \u0440\u0430\u0437\u0431\u0438\u0435\u043d\u0438\u044f \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f \u043d\u0430 \u0441\u0443\u043f\u0435\u0440\u043f\u0438\u043a\u0441\u0435\u043b\u0438. \u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c SLIC. \u0420\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u0438\u043a\u0438 \u043d\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u044e \u0442\u0435\u043a\u0441\u0442\u043e\u0432.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Intro":{"id":"Machine-learning/Complex-models-interpretation/Intro","title":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u0441\u043b\u043e\u0436\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439","description":"\u0421\u043f\u043e\u0441\u043e\u0431\u044b \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u0438 \u0441\u043b\u043e\u0436\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f (black-box model interpretation). \u041e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u0435 \u043f\u043e\u0434\u0445\u043e\u0434\u043e\u0432, \u0432\u044b\u0437\u0432\u0430\u043d\u043d\u043e\u0435 \u0442\u0435\u043c, \u0447\u0442\u043e \u043a\u043e\u0440\u0440\u0435\u043b\u044f\u0446\u0438\u044f \u043d\u0435 \u0432\u0441\u0435\u0433\u0434\u0430 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e-\u0441\u043b\u0435\u0434\u0441\u0442\u0432\u0435\u043d\u043d\u0443\u044e \u0441\u0432\u044f\u0437\u044c (correlation does not imply causation).","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/LIME":{"id":"Machine-learning/Complex-models-interpretation/LIME","title":"\u041b\u043e\u043a\u0430\u043b\u044c\u043d\u043e\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0435 \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u0443\u0435\u043c\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u044c\u044e","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c LIME \u0434\u043b\u044f \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u044f \u0438 \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0441\u043b\u043e\u0436\u043d\u044b\u043c\u0438 \u043c\u043e\u0434\u0435\u043b\u044f\u043c\u0438, \u0442\u0430\u043a\u0438\u043c\u0438 \u043a\u0430\u043a \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438. \u041e\u0441\u043e\u0431\u0435\u043d\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u0438 \u043f\u0440\u0438\u043c\u0435\u0440 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Permutation-feature-importance":{"id":"Machine-learning/Complex-models-interpretation/Permutation-feature-importance","title":"\u0412\u043b\u0438\u044f\u043d\u0438\u0435 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u043d\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432","description":"\u0410\u043d\u0430\u043b\u0438\u0437 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043f\u043e \u0432\u043b\u0438\u044f\u043d\u0438\u044e \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u0430 \u043d\u0430 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c \u043c\u043e\u0434\u0435\u043b\u0435\u0439. \u041c\u0435\u0442\u043e\u0434\u043e\u043c \u043f\u0435\u0440\u0435\u0441\u0442\u0430\u043d\u043e\u0432\u043e\u0447\u043d\u043e\u0439 \u0432\u0430\u0436\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 (permutation feature importance). \u041f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430 \u0438 \u043d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043a\u0438 \u043c\u0435\u0442\u043e\u0434\u0430. \u041f\u0440\u0438\u043c\u0435\u0440 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Prototypes-criticisms":{"id":"Machine-learning/Complex-models-interpretation/Prototypes-criticisms","title":"\u041f\u0440\u043e\u0433\u043d\u043e\u0437\u044b \u043d\u0430 \u0442\u0438\u043f\u0438\u0447\u043d\u044b\u0445 \u0438 \u043d\u0435\u0442\u0438\u043f\u0438\u0447\u043d\u044b\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u0430\u0445","description":"\u041c\u0435\u0442\u043e\u0434 \u0430\u043d\u0430\u043b\u0438\u0437\u0430 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043d\u0430 \u0442\u0438\u043f\u0438\u0447\u043d\u044b\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u0430\u0445 (\u043f\u0440\u043e\u0442\u043e\u0442\u0438\u043f\u0430\u0445) \u0438 \u043d\u0435\u0442\u0438\u043f\u0438\u0447\u043d\u044b\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u0430\u0445 (\u043a\u0440\u0438\u0442\u0438\u043a\u0430\u0445). \u041c\u0435\u0442\u043e\u0434\u044b \u0432\u044b\u0434\u0435\u043b\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0442\u043e\u0442\u0438\u043f\u043e\u0432 \u0438 \u043a\u0440\u0438\u0442\u0438\u043a\u043e\u0432.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Questions":{"id":"Machine-learning/Complex-models-interpretation/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u0438 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Shapley-values":{"id":"Machine-learning/Complex-models-interpretation/Shapley-values","title":"\u0417\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0428\u0435\u043f\u043b\u0438","description":"\u0417\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u0428\u0435\u043f\u043b\u0438 (Shapley values) \u0434\u043b\u044f \u043e\u0446\u0435\u043d\u043a\u0438 \u0432\u0430\u0436\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u043a\u0430\u043a \u0434\u043b\u044f \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0430, \u0442\u0430\u043a \u0438 \u0432 \u0446\u0435\u043b\u043e\u043c \u043f\u043e \u0432\u044b\u0431\u043e\u0440\u043a\u0435. \u041f\u0440\u0438\u043c\u0435\u0440 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0438 \u0444\u043e\u0440\u043c\u0443\u043b\u0430 \u0434\u043b\u044f \u0440\u0430\u0441\u0447\u0451\u0442\u0430.","sidebar":"Machine-learning"},"Machine-learning/Complex-models-interpretation/Training-object-importance":{"id":"Machine-learning/Complex-models-interpretation/Training-object-importance","title":"\u0412\u043b\u0438\u044f\u043d\u0438\u0435 \u043e\u0431\u0443\u0447\u0430\u044e\u0449\u0438\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432","description":"\u0410\u043d\u0430\u043b\u0438\u0437 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0437\u0430 \u0441\u0447\u0451\u0442 \u043e\u0446\u0435\u043d\u043a\u0438 \u0432\u043b\u0438\u044f\u043d\u0438\u044f \u043d\u0430 \u043d\u0438\u0445 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u044b\u0445 \u043e\u0431\u0443\u0447\u0430\u044e\u0449\u0438\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432. \u041f\u0440\u0438\u043c\u0435\u0440\u044b \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u044d\u0442\u043e\u0433\u043e \u043f\u043e\u0434\u0445\u043e\u0434\u0430 \u0434\u043b\u044f \u043b\u0443\u0447\u0448\u0435\u0439 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Categorical-preprocessing":{"id":"Machine-learning/Data-preprocessing/Categorical-preprocessing","t
1itle":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u043a\u0430\u0442\u0435\u0433\u043e\u0440\u0438\u0430\u043b\u044c\u043d\u044b\u0445 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043a\u0430\u0442\u0435\u0433\u043e\u0440\u0438\u0430\u043b\u044c\u043d\u044b\u0445 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u043f\u0440\u0438 \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043a\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. Ordinal encoding, frequency encoding, one-hot encoding, mean value encoding, cyclic encoding.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Data-imputation":{"id":"Machine-learning/Data-preprocessing/Data-imputation","title":"\u0417\u0430\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u043f\u0440\u043e\u043f\u0443\u0441\u043a\u043e\u0432 \u0432 \u0434\u0430\u043d\u043d\u044b\u0445","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u0437\u0430\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u043f\u0443\u0441\u043a\u043e\u0432 \u0432 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u0432\u0435\u0449\u0435\u0441\u0442\u0432\u0435\u043d\u043d\u044b\u0445, \u0431\u0438\u043d\u0430\u0440\u043d\u044b\u0445 \u0438 \u043a\u0430\u0442\u0435\u0433\u043e\u0440\u0438\u0430\u043b\u044c\u043d\u044b\u0445 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u043f\u0435\u0440\u0435\u0434 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u043e\u0439.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Feature-generation":{"id":"Machine-learning/Data-preprocessing/Feature-generation","title":"\u0413\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u044f \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432","description":"\u041f\u043e\u0434\u0445\u043e\u0434\u044b \u043a \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0438 \u043d\u043e\u0432\u044b\u0445 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 (feature engineering) \u043d\u0430 \u044d\u0442\u0430\u043f\u0435 \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043a\u0438 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Feature-normalization":{"id":"Machine-learning/Data-preprocessing/Feature-normalization","title":"\u041d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432","description":"\u041d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u0434\u043b\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u041f\u043e\u043d\u044f\u0442\u0438\u0435 \u043c\u0435\u0434\u0438\u0430\u043d\u044b, \u043a\u0432\u0430\u043d\u0442\u0438\u043b\u0438 \u0438 \u043f\u0435\u0440\u0441\u0435\u043d\u0442\u0438\u043b\u0438.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Feature-reduction":{"id":"Machine-learning/Data-preprocessing/Feature-reduction","title":"\u0421\u043e\u043a\u0440\u0430\u0449\u0435\u043d\u0438\u0435 \u0447\u0438\u0441\u043b\u0430 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432","description":"\u041e\u0442\u0431\u043e\u0440 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 (feature selection) \u0438 \u0441\u043d\u0438\u0436\u0435\u043d\u0438\u0435 \u0440\u0430\u0437\u043c\u0435\u0440\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432\u043e\u0433\u043e \u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0441\u0442\u0432\u0430 (dimensionality reduction) \u043f\u0440\u0438 \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043a\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"}
1,"Machine-learning/Data-preprocessing/Outlier-filtering":{"id":"Machine-learning/Data-preprocessing/Outlier-filtering","title":"\u0424\u0438\u043b\u044c\u0442\u0440\u0430\u0446\u0438\u044f \u0432\u044b\u0431\u0440\u043e\u0441\u043e\u0432","description":"\u0417\u0430\u0434\u0430\u0447\u0430 \u0444\u0438\u043b\u044c\u0442\u0440\u0430\u0446\u0438\u044f \u0432\u044b\u0431\u0440\u043e\u0441\u043e\u0432 (\u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u0430\u043d\u043e\u043c\u0430\u043b\u0438\u0439) \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Preprocessing-text-data":{"id":"Machine-learning/Data-preprocessing/Preprocessing-text-data","title":"\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0442\u0435\u043a\u0441\u0442\u043e\u0432\u044b\u0445 \u0434\u0430\u043d\u043d\u044b\u0445","description":"\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0442\u0435\u043a\u0441\u0442\u043e\u0432\u044b\u0445 \u0434\u0430\u043d\u043d\u044b\u0445 \u0432 \u0432\u0438\u0434\u0435 \u0432\u0435\u043a\u0442\u043e\u0440\u0430 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u0434\u043b\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0435\u0448\u043a\u0430 \u0441\u043b\u043e\u0432. \u041c\u0435\u0442\u043e\u0434 TF-IDF.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Questions":{"id":"Machine-learning/Data-preprocessing/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438 \u043f\u043e \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043a\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u043f\u0435\u0440\u0435\u0434 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435\u043c \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Target-processing":{"id":"Machine-learning/Data-preprocessing/Target-processing","title":"\u041f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u0446\u0435\u043b\u0435\u0432\u043e\u0439 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439","description":"\u041f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u0446\u0435\u043b\u0435\u0432\u043e\u0439 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439 \u0434\u043b\u044f \u043f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u044f \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432.","sidebar":"Machine-learning"},"Machine-learning/Data-preprocessing/Time-preprocessing":{"id":"Machine-learning/Data-preprocessing/Time-preprocessing","title":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0432\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0433\u043e \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u0430","description":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0432\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0433\u043e \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u0430 \u043f\u0440\u0438 \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043a\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u0423\u0447\u0451\u0442 \u0442\u0440\u0435\u043d\u0434\u0430 \u0438 \u0441\u0435\u0437\u043e\u043d\u043d\u043e\u0441\u0442\u0438.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Advanced-trees":{"id":"Machine-learning/Decision-trees/Advanced-trees","title":"\u041e\u0431\u043e\u0431\u0449\u0435\u043d\u0438\u044f \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432","description":"\u041e\u0431\u043e\u0431\u0449\u0435\u043d\u0438\u044f \u0438 \u0443\u0441\u043b\u043e\u0436\u043d\u0435\u043d\u0438\u044f \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0430 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432 (decision trees).","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Custom-loss-function":{"id":"Machine-learning/Decision-trees/Custom-loss-function","title":"\u0423\u0447\u0451\u0442 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u043e\u0439 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043f\u043e\u0442\u0435\u0440\u044c","de
1scription":"\u041e\u0431\u043e\u0441\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043d\u0435\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0451\u043d\u043d\u043e\u0441\u0442\u0438 (impurity functions) \u043f\u0440\u0438 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0435 \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430 \u043a\u0430\u043a \u043c\u0438\u043d\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u043e\u0432 \u043f\u043e\u0442\u0435\u0440\u044c \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0451\u043d\u043d\u043e\u0433\u043e \u0432\u0438\u0434\u0430. \u041e\u0431\u043e\u0441\u043d\u043e\u0432\u0430\u043d\u0438\u044f \u0434\u043b\u044f \u0434\u0438\u0441\u043f\u0435\u0440\u0441\u0438\u0438, \u0441\u0440\u0435\u0434\u043d\u0435\u0433\u043e \u0430\u0431\u0441\u043e\u043b\u044e\u0442\u043d\u043e\u0433\u043e \u043e\u0442\u043a\u043b\u043e\u043d\u0435\u043d\u0438\u044f, \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u043e\u043d\u043d\u043e\u0439 \u043e\u0448\u0438\u0431\u043a\u0438, \u043a\u0440\u0438\u0442\u0435\u0440\u0438\u044f \u0414\u0436\u0438\u043d\u0438 \u0438 \u044d\u043d\u0442\u0440\u043e\u043f\u0438\u0439\u043d\u043e\u0433\u043e \u043a\u0440\u0438\u0442\u0435\u0440\u0438\u044f. \u0421\u043b\u0443\u0447\u0430\u0439 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u043e\u0439 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043f\u043e\u0442\u0435\u0440\u044c.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Decision-trees":{"id":"Machine-learning/Decision-trees/Decision-trees","title":"\u0420\u0435\u0448\u0430\u044e\u0449\u0438\u0435 \u0434\u0435\u0440\u0435\u0432\u044c\u044f","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432 (decision trees) \u0432 \u0437\u0430\u0434\u0430\u0447\u0430\u0445 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f. CART, \u04214.5, ID3. \u041f\u0440\u0438\u043c\u0435\u0440 \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430. \u0421\u0432\u044f\u0437\u044c \u0441 \u043f\u0440\u0430\u0432\u0438\u043b\u043e\u0432\u044b\u043c\u0438 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0430\u043c\u0438 (rule induction).","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Feature-importances":{"id":"Machine-learning/Decision-trees/Feature-importances","title":"\u0412\u0430\u0436\u043d\u043e\u0441\u0442\u044c \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432","description":"\u041e\u0446\u0435\u043d\u043a\u0430 \u0432\u0430\u0436\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 (feature importance), \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0435 \u0434\u0435\u0440\u0435\u0432\u043e - \u043c\u0435\u0442\u043e\u0434 mean decrease in impurity.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Impurity-functions":{"id":"Machine-learning/Decision-trees/Impurity-functions","title":"\u0424\u0443\u043d\u043a\u0446\u0438\u0438 \u043d\u0435\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0451\u043d\u043d\u043e\u0441\u0442\u0438 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432","description":"\u0424\u0443\u043d\u043a\u0446\u0438\u0438 \u043d\u0435\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0451\u043d\u043d\u043e\u0441\u0442\u0438 (impurity functions) \u0434\u043b\u044f \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432. \u0418\u0445 \u043c\u043e\u0442\u0438\u0432\u0430\u0446\u0438\u044f \u0438 \u0441\u0432\u043e\u0439\u0441\u0442\u0432\u0430. \u041a\u0440\u0438\u0442\u0435\u0440\u0438\u0439 \u0414\u0436\u0438\u043d\u0438, \u044d\u043d\u0442\u0440\u043e\u043f\u0438\u0439\u043d\u044b\u0439 \u043a\u0440\u0438\u0442\u0435\u0440\u0438\u0439 \u0438 \u043a\u0440\u0438\u0442\u0435\u0440\u0438\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u043e\u043d\u043d\u043e\u0439 \u043e\u0448\u0438\u0431\u043a\u0438.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Literature":{"id":"Machine-learning/Decision-trees/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u043c\u0435\u0442\u043e\u0434\u0430\u043c \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Missing-values":{"id":"Machine-learning/Decision-trees/Missing-values","title":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u043f\u0440\u043e\u043f\u0443\u0449\u0435\u043d\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u0437\u0430\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u043f\u0443\u0449\u0435\u043d\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u0432 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0435 \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Questions":{"id":"Machine-learning/Decision-trees/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u043c \u0434\u0435\u0440\u0435\u0432\u044c\u044f\u043c.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Regression-classification-examples":{"id":"Machine-learning/Decision-trees/Regression-classification-examples","title":"\u041e\u0441\u043e\u0431\u0435\u043d\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430","description":"\u041e\u0441\u043e\u0431\u0435\u043d\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u043c\u0438 \u0434\u0435\u0440\u0435\u0432\u044c\u044f\u043c\u0438 \u0432 \u0437\u0430\u0434\u0430\u0447\u0430\u0445 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438 \u0438 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438. \u
10412\u0437\u0430\u0438\u043c\u043d\u043e\u0435 \u0434\u043e\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432 \u0438 \u043b\u0438\u043d\u0435\u0439\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Tree-benefits":{"id":"Machine-learning/Decision-trees/Tree-benefits","title":"\u0410\u043d\u0430\u043b\u0438\u0437 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432","description":"\u041f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430 \u0438 \u043d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043a\u0438 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432 (decision trees) \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Tree-fitting":{"id":"Machine-learning/Decision-trees/Tree-fitting","title":"\u041d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0430 \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430 (decision tree fitting). \u0412\u044b\u0431\u043e\u0440 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u043f\u0440\u0430\u0432\u0438\u043b \u0432\u043e \u0432\u043d\u0443\u0442\u0440\u0435\u043d\u043d\u0438\u0445 \u0443\u0437\u043b\u0430\u0445 \u0438 \u043d\u0430\u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0430 \u0432 \u043b\u0438\u0441\u0442\u043e\u0432\u044b\u0445 \u0432\u0435\u0440\u0448\u0438\u043d\u0430\u0445 \u0434\u0435\u0440\u0435\u0432\u0430.","sidebar":"Machine-learning"},"Machine-learning/Decision-trees/Tree-pruning":{"id":"Machine-learning/Decision-trees/Tree-pruning","title":"\u041e\u0431\u0440\u0435\u0437\u043a\u0430 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u043e\u0431\u0440\u0435\u0437\u043a\u0438 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432 (tree pruning) \u0434\u043b\u044f \u043f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u044f \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0440\u0435\u0448\u0430\u044e\u0449\u0438\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432. \u041c\u0435\u0442\u043e\u0434 \u043e\u0431\u0440\u0435\u0437\u043a\u0438 \u043f\u043e \u043c\u0438\u043d\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0439 \u0446\u0435\u043d\u0435 (minimal cost-complexity pruning).","sidebar":"Machine-learning"},"Machine-learning/Dimensionality-reduction/Dimensionality-reduction":{"id":"Machine-learning/Dimensionality-reduction/Dimensionality-reduction","title":"\u0421\u043d\u0438\u0436\u0435\u043d\u0438\u0435 \u0440\u0430\u0437\u043c\u0435\u0440\u043d\u043e\u0441\u0442\u0438","description":"\u0412\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u0432 \u043c\u0435\u0442\u043e\u0434\u044b \u0441\u043d\u0438\u0436\u0435\u043d\u0438\u044f \u0440\u0430\u0437\u043c\u0435\u0440\u043d\u043e\u0441\u0442\u0438.","sidebar":"Machine-learning"},"Machine-learning/Dimensionality-reduction/Features-of-PCA":{"id":"Machine-learning/Dimensionality-reduction/Features-of-PCA","title":"\u0421\u0432\u043e\u0439\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0435\u043a\u0446\u0438\u0439 \u043d\u0430 \u0433\u043b\u0430\u0432\u043d\u044b\u0435 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u044b","description":"\u0421\u0432\u043e\u0439\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0435\u043a\u0446\u0438\u0439 \u043d\u0430 \u0433\u043b\u0430\u0432\u043d\u044b\u0435 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u044b.","sidebar":"Machine-learning"},"Machine-learning/Dimensionality-reduction/Finding-principal-components":{"id":"Machine-learning/Dimensionality-reduction/Finding-principal-components","title":"\u041d\u0430\u0445\u043e\u0436\u0434\u0435\u043d\u0438\u0435 \u0433\u043b\u0430\u0432\u043d\u044b\u0445 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442","description":"\u0410\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0432\u044b\u0432\u043e\u0434 \u0433\u043b\u0430\u0432\u043d\u044b\u0445 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442 \u0432 \u043c\u0435\u0442\u043e\u0434\u0435 PCA.","sidebar":"Machine-learning"},"Machine-learning/Dimensionality-reduction/Global-optimality-of-PCA":{"id":"Machine-learning/Dimensionality-reduction/Global-optimality-of-PCA","title":"\u0413\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0430\u044f \u043e\u043f\u0442\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u044c \u0433\u043b\u0430\u0432\u043d\u044b\u0445 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442","description":"\u0413\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0430\u044f \u043e\u043f\u0442\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u044c \u0433\u043b\u0430\u0432\u043d\u044b\u0445 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442.","sidebar":"Machine-learning"},"Machine-learning/Dimensionality-reduction/LDA-dimensionality-reduction":{"id":"Machine-learning/Dimensionality-reduction/LDA-dimensionality-reduction","title":"\u0421\u043d\u0438\u0436\u0435\u043d\u0438\u0435 \u0440\u0430\u0437\u043c\u0435\u0440\u043d\u043e\u0441\u0442\u0438 \u043c\u0435\u0442\u043e\u0434\u043e\u043c LDA","description":"\u0421\u043d\u0438\u0436\u0435\u043d\u0438\u0435 \u0440\u0430\u0437\u043c\u0435\u0440\u043d\u043e\u0441\u0442\u0438 \u0441 \u0443\u0447\u0438\u0442\u0435\u043b\u0435\u043c \u043c\u0435\u0442\u043e\u0434\u043e\u043c LDA.","sidebar":"Machine-learning"},"Machine-learning/Dimensionality-reduction/Principal-component-analysis":{"id":"Machine-learning/Dimensionality-reduction/Principal-component-analysis","title":"\u041c\u0435\u0442\u043e\u0434 \u0433\u043b\u0430\u0432\u043d\u044b\u0445 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442","description":"\u041c\u0435\u0442\u043e\u0434 \u0433\u043b\u0430\u0432\u043d\u044b\u0445 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442.","sidebar":"Machine-learning"},"Machine-learning/Dimensionality-reduction/Topic-modelling":{"i
1d":"Machine-learning/Dimensionality-reduction/Topic-modelling","title":"\u0422\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435","description":"\u0422\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0442\u0435\u043a\u0441\u0442\u043e\u0432.","sidebar":"Machine-learning"},"Machine-learning/General-classifiers/Discriminant-functions":{"id":"Machine-learning/General-classifiers/Discriminant-functions","title":"\u041e\u0431\u0449\u0438\u0439 \u0432\u0438\u0434 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u044e\u0449\u0438\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439","description":"\u0417\u0430\u0434\u0430\u0447\u0430 \u0440\u0435\u0433\u0440\u0435\u0441\u0438\u0438 \u0438 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438 \u0432 \u043e\u0431\u0449\u0435\u043c \u0432\u0438\u0434\u0435. \u0414\u0438\u0441\u043a\u0440\u0438\u043c\u0438\u043d\u0430\u043d\u0442\u043d\u044b\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 (\u0440\u0435\u0439\u0442\u0438\u043d\u0433\u0438 \u043a\u043b\u0430\u0441\u0441\u043e\u0432).","sidebar":"Machine-learning"},"Machine-learning/General-classifiers/Margin":{"id":"Machine-learning/General-classifiers/Margin","title":"\u041e\u0442\u0441\u0442\u0443\u043f \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438","description":"\u041e\u0446\u0435\u043d\u043a\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0432 \u0437\u0430\u0434\u0430\u0447\u0435 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438. \u0424\u0443\u043d\u043a\u0446\u0438\u044f \u043f\u043e\u0442\u0435\u0440\u044c, \u043e\u0442\u0441\u0442\u0443\u043f \u0432 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438 (margin).","sidebar":"Machine-learning"},"Machine-learning/General-classifiers/Probability-prediction-SoftMax":{"id":"Machine-learning/General-classifiers/Probability-prediction-SoftMax","title":"\u041f\u0440\u0435\u0434\u0441\u043a\u0430\u0437\u0430\u043d\u0438\u0435 \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u043e\u0441\u0442\u0435\u0439 \u0438 \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u0435 SoftMax","description":"SoftMax \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u0435 - 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1043e\u0433\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f \u0434\u043b\u044f \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u043c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Linear-classification/Questions":{"id":"Machine-learning/Linear-classification/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u043c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u0438\u043c \u043c\u0435\u0442\u043e\u0434\u0430\u043c \u0438 \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Linear-classification/SVM":{"id":"Machine-learning/Linear-classification/SVM","title":"\u041c\u0435\u0442\u043e\u0434 \u043e\u043f\u043e\u0440\u043d\u044b\u0445 \u0432\u0435\u043a\u0442\u043e\u0440\u043e\u0432","description":"\u041c\u0435\u0442\u043e\u0434 \u043e\u043f\u043e\u0440\u043d\u044b\u0445 \u0432\u0435\u043a\u0442\u043e\u0440\u043e\u0432 (support vector machine, SVM) \u0434\u043b\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438. \u0415\u0433\u043e \u0433\u0435\u043e\u043c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043e\u0431\u043e\u0441\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u0438 \u043e\u0431\u043e\u0431\u0449\u0435\u043d\u0438\u0435 \u0447\u0435\u0440\u0435\u0437 \u044f\u0434\u0440\u0430 \u041c\u0435\u0440\u0441\u0435\u0440\u0430 (kernel trick).","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Analytic-solution":{"id":"Machine-learning/Linear-regression-extensions/Analytic-solution","title":"\u0410\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u0440\u0435\u0448\u0435\u043d\u0438\u0435 \u0434\u043b\u044f \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438","description":"\u041c\u0435\u0442\u043e\u0434 \u043d\u0430\u0438\u043c\u0435\u043d\u044c\u0448\u0438\u0445 \u043a\u0432\u0430\u0434\u0440\u0430\u0442\u043e\u0432 (\u041c\u041d\u041a-\u043e\u0446\u0435\u043d\u043a\u0430)-\u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0432\u044b\u0432\u043e\u0434 \u043e\u043f\u0442\u0438\u043c\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0434\u043b\u044f \u043a\u043e\u044d\u0444\u0444\u0438\u0446\u0438\u0435\u043d\u0442\u043e\u0432 \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Linear-composition":{"id":"Machine-learning/Linear-regression-extensions/Linear-composition","title":"\u041b\u0438\u043d\u0435\u0439\u043d\u044b\u0439 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044c \u043c\u043e\u0434\u0435\u043b\u0435\u0439","description":"\u041f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u0435 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0447\u0435\u0440\u0435\u0437 \u0438\u0445 \u043b\u0438\u043d\u0435\u0439\u043d\u0443\u044e \u043a\u043e\u043c\u0431\u0438\u043d\u0430\u0446\u0438\u044e. \u0421\u043f\u043e\u0441\u043e\u0431\u044b \u0440\u0435\u0433\u0443\u043b\u044f\u0440\u0438\u0437\u0430\u0446\u0438\u0438 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044f.","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Linear-regression":{"id":"Machine-learning/Linear-regression-extensions/Linear-regression","title":"\u041b\u0438\u043d\u0435\u0439\u043d\u0430\u044f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f","description":"\u041c\u043e\u0434\u0435\u043b\u044c \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 - \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435, \u043f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u0438\u044f, \u0434\u043e\u0441\u0442\u043e\u0438\u043d\u0441\u0442\u0432\u0430 \u0438 \u043d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043a\u0438.","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Literature":{"id":"Machine-learning/Linear-regression-extensions/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Local-linear-regression":{"id":"Machine-learning/Linear-regression-extensions/Local-linear-regression","title":"\u041b\u
1043e\u043a\u0430\u043b\u044c\u043d\u043e-\u043b\u0438\u043d\u0435\u0439\u043d\u0430\u044f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f","description":"\u041b\u043e\u043a\u0430\u043b\u044c\u043d\u043e-\u043b\u0438\u043d\u0435\u0439\u043d\u0430\u044f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f (LOWESS) - \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 \u0438 \u0441\u0432\u043e\u0439\u0441\u0442\u0432\u0430.","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Orthogonal-matching-pursuit":{"id":"Machine-learning/Linear-regression-extensions/Orthogonal-matching-pursuit","title":"Orthogonal matching pursuit","description":"\u041c\u0435\u0442\u043e\u0434 orthogonal matching pursuit \u0441 \u043f\u043e\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u043d\u044b\u043c \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0435\u043c \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u0432 \u043c\u043e\u0434\u0435\u043b\u044c \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Questions":{"id":"Machine-learning/Linear-regression-extensions/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Regularization-in-linear-regression":{"id":"Machine-learning/Linear-regression-extensions/Regularization-in-linear-regression","title":"\u0420\u0435\u0433\u0443\u043b\u044f\u0440\u0438\u0437\u0430\u0446\u0438\u044f \u0432 \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438","description":"\u0420\u0435\u0433\u0443\u043b\u044f\u0440\u0438\u0437\u0430\u0446\u0438\u044f \u0432 \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438. \u041c\u0435\u0442\u043e\u0434\u044b \u0440\u0435\u0433\u0443\u043b\u044f\u0440\u0438\u0437\u0430\u0446\u0438\u0438 \u0438 \u0438\u0445 \u0441\u0432\u043e\u0439\u0441\u0442\u0432\u0430.","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Ridge-regression-solution":{"id":"Machine-learning/Linear-regression-extensions/Ridge-regression-solution","title":"\u0410\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u0440\u0435\u0448\u0435\u043d\u0438\u0435 \u0434\u043b\u044f \u0433\u0440\u0435\u0431\u043d\u0435\u0432\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438","description":"\u0410\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0432\u044b\u0432\u043e\u0434 \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u0434\u043b\u044f \u043a\u043e\u044d\u0444\u0444\u0438\u0446\u0438\u0435\u043d\u0442\u043e\u0432 \u0433\u0440\u0435\u0431\u043d\u0435\u0432\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Linear-regression-extensions/Support-vector-regression":{"id":"Machine-learning/Linear-regression-extensions/Support-vector-regression","title":"\u0420\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f \u043e\u043f\u043e\u0440\u043d\u044b\u0445 \u0432\u0435\u043a\u0442\u043e\u0440\u043e\u0432","description":"\u041c\u0435\u0442\u043e\u0434 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u043e\u043f\u043e\u0440\u043d\u044b\u0445 \u0432\u0435\u043a\u0442\u043e\u0440\u043e\u0432 - \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435, \u0438\u043d\u0442\u0443\u0438\u0446\u0438\u044f, \u043e\u0431\u043e\u0431\u0449\u0435\u043d\u0438\u0435 \u0447\u0435\u0440\u0435\u0437 \u044f\u0434\u0440\u0430 \u041c\u0435\u0440\u0441\u0435\u0440\u0430 (kernel trick). \u041e\u043f\u043e\u0440\u043d\u044b\u0435 \u0438 \u043d\u0435\u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u0432\u043d\u044b\u0435 \u043e\u0431\u044a\u0435\u043a\u0442\u044b.","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/Distance-functions":{"id":"Machine-learning/Metric-methods/Distance-functions","title":"\u0424\u0443\u043d\u043a\u0446\u0438\u0438 \u0440\u0430\u0441\u0441\u0442\u043e\u044f\u043d\u0438\u044f","description":"\u041f\u043e\u043f\u0443\u043b\u044f\u0440\u043d\u044b\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u0440\u0430\u0441\u0441\u0442\u043e\u044f\u043d\u0438\u044f \u0438 \u043c\u0435\u0440\u044b \u0431\u043b\u0438\u0437\u043e\u0441\u0442\u0438 \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438. \u
1041a\u043e\u0441\u0438\u043d\u0443\u0441\u043d\u0430\u044f \u043c\u0435\u0440\u0430 \u0431\u043b\u0438\u0437\u043e\u0441\u0442\u0438, \u0440\u0430\u0441\u0441\u0442\u043e\u044f\u043d\u0438\u0435 \u041c\u0430\u0445\u0430\u043b\u0430\u043d\u043e\u0431\u0438\u0441\u0430, \u043c\u0435\u0440\u0430 \u0431\u043b\u0438\u0437\u043e\u0441\u0442\u0438 \u0416\u0430\u043a\u043a\u0430\u0440\u0430, \u0440\u0435\u0434\u0430\u043a\u0442\u043e\u0440\u0441\u043a\u043e\u0435 \u0440\u0430\u0441\u0441\u0442\u043e\u044f\u043d\u0438\u0435. \u041c\u0435\u0442\u043e\u0434\u044b \u0441\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u044f \u0432\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445 \u0440\u044f\u0434\u043e\u0432.","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/KNN":{"id":"Machine-learning/Metric-methods/KNN","title":"\u041c\u0435\u0442\u043e\u0434 K \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0441\u043e\u0441\u0435\u0434\u0435\u0439","description":"\u041c\u0435\u0442\u043e\u0434 K \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0441\u043e\u0441\u0435\u0434\u0435\u0439 (K nearest neighbors) \u0434\u043b\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0438 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/KNN-analysis":{"id":"Machine-learning/Metric-methods/KNN-analysis","title":"\u0410\u043d\u0430\u043b\u0438\u0437 \u043c\u0435\u0442\u043e\u0434\u0430 K \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0441\u043e\u0441\u0435\u0434\u0435\u0439","description":"\u041f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430 \u0438 \u043d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043a\u0438 \u043c\u0435\u0442\u043e\u0434\u0430 K \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0441\u043e\u0441\u0435\u0434\u0435\u0439. \u041f\u043e\u043d\u044f\u0442\u0438\u0435 \u043f\u0440\u043e\u043a\u043b\u044f\u0442\u0438\u044f \u0440\u0430\u0437\u043c\u0435\u0440\u043d\u043e\u0441\u0442\u0438 (curse of dimensionality).","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/Local-constant-regression":{"id":"Machine-learning/Metric-methods/Local-constant-regression","title":"\u041b\u043e\u043a\u0430\u043b\u044c\u043d\u043e-\u043f\u043e\u0441\u0442\u043e\u044f\u043d\u043d\u0430\u044f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f","description":"\u0420\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f \u041d\u0430\u0434\u0430\u0440\u0430\u044f-\u0412\u0430\u0442\u0441\u043e\u043d\u0430, \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u043e-\u043f\u043e\u0441\u0442\u043e\u044f\u043d\u043d\u0430\u044f \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f - \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u0430 \u0438 \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u044b.","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/Metric-methods":{"id":"Machine-learning/Metric-methods/Metric-methods","title":"\u041c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u044b","description":"\u041c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u044b \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0434\u043b\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0438 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/Nearest-centroids":{"id":"Machine-learning/Metric-methods/Nearest-centroids","title":"\u041c\u0435\u0442\u043e\u0434 \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0446\u0435\u043d\u0442\u0440\u043e\u0438\u0434\u043e\u0432","description":"\u041c\u0435\u0442\u043e\u0434 \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0446\u0435\u043d\u0442\u0440\u043e\u0438\u0434\u043e\u0432 (nearest centroids) \u0434\u043b\u044f \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/Questions":{"id":"Machine-learning/Metric-methods/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/Weighted-KNN":{"id":"Machine-learning/Metric-methods/Weighted-KNN","title":"\u041e\u0431\u043e\u0431\u0449\u0435\u043d\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u0430 K \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0441\u043e\u0441\u0435\u0434\u0435\u0439 \u0441 \u0432\u0435\u0441\u0430\u043c\u0438","description":"\u041e\u0431\u043e\u0431\u0449\u0435\u043d\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u0430 K \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0441\u043e\u0441\u0435\u0434\u0435\u0439 \u0437\u0430 \u0441\u0447\u0451\u0442 \u0432\u0437\u0432\u0435\u0448\u0435\u043d\u043d\u043e\u0433\u043e \u0443\u0447\u0451\u0442\u0430 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432.","sidebar":"Machine-learning"},"Machine-learning/Metric-methods/Weights-selection":{"id":"Machine-learning/Metric-methods/Weights-selection","title":"\u0412\u0435\u0441\u0430 \u0432 \u043c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u0435\u0442\u043e\u0434\u0430\u0445","description":"\u0412\u044b\u0431\u043e\u0440 \u0432\u0435\u0441\u043e\u0432, \u0441 \u043a\u043e\u0442\u043e\u0440\u044b\u043c\u0438 \u0443\u0447\u0438\u0442\u044b\u0432\u0430\u044e\u0442\u0441\u044f \u043e\u0431\u044a\u0435\u043a\u0442\u044b \u043e\u0431\u0443\u0447\u0430\u044e\u0449\u0435\u0439 \u0432\u044b\u0431\u043e\u0440\u043a\u0438 \u043f\u0440\u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u0435\u0442\u043e\u0434\u043e\u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/Averaging-ensembles":{"id":"Machine-learning/Model-ensembles/Averaging-ensembles","title":"\u041f\u0440\u043e\u0441\u0442\u0430\u044f \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u044f \u0432 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044f\u0445","description":"\u041f\u0440\u043e\u0441\u0442\u044b\u0435 c\u043f\u043e\u0441\u043e\u0431\u044b \u043e\u0431\u044a\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0432 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044f\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439. \u0413\u043e\u043b\u043e\u0441\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u043e \u0431\u043e\u043b\u044c\u0448\u0438\u043d\u0441\u0442\u0432\u0443, \u0443\u0441\u0440\u0435\u0434\u043d\u0435\u043d\u0438\u0435 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432, \u0443\u0441\u0440\u0435\u0434\u043d\u0435\u043d\u0438\u0435 \u0440\u0435\u0439\u0442\u0438\u043d\u0433\u043e\u0432 \u0411\u0440\u0438\u0435\u0440\u0430.","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/Base-models-building":{"id":"Machine-learning/Model-ensembles/Base-models-building","t
1itle":"\u041c\u0435\u0442\u043e\u0434\u044b \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u0431\u0430\u0437\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439","description":"\u0421\u043f\u043e\u0441\u043e\u0431\u044b \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u0431\u0430\u0437\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0434\u043b\u044f \u0444\u043e\u0440\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 (model ensemble).","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/Literature":{"id":"Machine-learning/Model-ensembles/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u043c\u0435\u0442\u043e\u0434\u0430\u043c \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/Mathematical-justifications":{"id":"Machine-learning/Model-ensembles/Mathematical-justifications","title":"\u041c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043e\u0431\u043e\u0441\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u0435\u0439","description":"\u041f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u0435\u0439 \u043c\u043e\u0434\u0435\u043b\u0435\u0439. \u0414\u043e\u043a\u0430\u0437\u0430\u0442\u0435\u043b\u044c\u0441\u0442\u0432\u0430, \u0447\u0442\u043e \u043c\u043e\u0436\u043d\u043e \u0438\u0437 \u043d\u0430\u0431\u043e\u0440\u0430 \u043d\u0435\u0442\u043e\u0447\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u043e\u0436\u043d\u043e \u043f\u043e\u0441\u0442\u0440\u043e\u0438\u0442\u044c \u0442\u043e\u0447\u043d\u044b\u0439 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044c \u0434\u043b\u044f \u0437\u0430\u0434\u0430\u0447 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0438 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/Model-ensembles":{"id":"Machine-learning/Model-ensembles/Model-ensembles","title":"\u0410\u043d\u0441\u0430\u043c\u0431\u043b\u0438 \u043c\u043e\u0434\u0435\u043b\u0435\u0439","description":"\u041f\u043e\u043d\u044f\u0442\u0438\u0435 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u0435\u0439 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 (model ensemble) \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438. \u041c\u043e\u0442\u0438\u0432\u0430\u0446\u0438\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u0435\u0439 \u0434\u043b\u044f \u0431\u043e\u0440\u044c\u0431\u044b \u0441 \u043f\u0435\u0440\u0435\u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435\u043c, \u043d\u0435\u0434\u043e\u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435\u043c \u0438 \u0432 \u0434\u0440\u0443\u0433\u0438\u0445 \u0441\u043b\u0443\u0447\u0430\u044f\u0445.","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/Questions":{"id":"Machine-learning/Model-ensembles/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044e \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439.","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/RF-ERT":{"id":"Machine-learning/Model-ensembles/RF-ERT","title":"\u0410\u043d\u0441\u0430\u043c\u0431\u043b\u0438 \u0440\u0430\u043d\u0434\u043e\u043c\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0441\u043b\u0443\u0447\u0430\u0439\u043d\u043e\u0433\u043e \u043b\u0435\u0441\u0430 (random forest) \u0438 \u043e\u0441\u043e\u0431\u043e \u0441\u043b\u0443\u0447\u0430\u0439\u043d\u044b\u0445 \u0434\u0435\u0440\u0435\u0432\u044c\u0435\u0432 (extra trees). \u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u043e\u0432 \u0438 \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u0433\u0438\u043f\u0435\u0440\u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u044b. \u041f\u0440\u0438\u043c\u0435\u0440\u044b \u0437\u0430\u043f\u0443\u0441\u043a\u0430 \u0432 sklearn.","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/Sample-based-base-models":{"id":"Machine-learning/Model-ensembles/Sample-based-base-models","title":"\u041d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0430 \u043d\u0430 \u0440\u0430\u0437\u043d\u044b\u0445 \u0444\u0440\u0430\u0433\u043c\u0435\u043d\u0442\u0430\u0445 \u043e\u0431\u0443\u0447\u0430\u044e\u0449\u0435\u0439 \u0432\u044b\u0431\u043e\u0440\u043a\u0438","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u0435\u0439 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043f\u043e \u043f\u043e\u0434\u0432\u044b\u0431\u043e\u0440\u043a\u0430\u043c \u0438\u0437 \u0438\u0441\u0445\u043e\u0434\u043d\u043e\u0439 \u043e\u0431\u0443\u0447\u0430\u044e\u0449\u0435\u0439 \u0432\u044b\u0431\u043e\u0440\u043a\u0438. \u
1041c\u0435\u0442\u043e\u0434\u044b bagging, random subspaces, random patches, pasting, cross-validation. \u0412\u043b\u0438\u044f\u043d\u0438\u0435 \u0447\u0438\u0441\u043b\u0430 \u0431\u0430\u0437\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043d\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u043e \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044f. \u041e\u0446\u0435\u043d\u043a\u0430 Out-of-Bag \u0434\u043b\u044f \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u044f \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u0435\u043c \u043c\u043e\u0434\u0435\u043b\u0435\u0439.","sidebar":"Machine-learning"},"Machine-learning/Model-ensembles/Stacking":{"id":"Machine-learning/Model-ensembles/Stacking","title":"\u0421\u0442\u044d\u043a\u0438\u043d\u0433","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0441\u0442\u044d\u043a\u0438\u043d\u0433\u0430 (stacking) \u0438 \u0431\u043b\u0435\u043d\u0434\u0438\u043d\u0433\u0430 (blending) \u0434\u043b\u044f \u043e\u0431\u044a\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0440\u0430\u0437\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0432 \u0430\u043d\u0441\u0430\u043c\u0431\u043b\u044c. \u041f\u0440\u0438\u043c\u0435\u0440 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0441\u0442\u044d\u043a\u0438\u043d\u0433\u0430 \u0432 sklearn.","sidebar":"Machine-learning"},"Machine-learning/Multiclass-with-binary-classifiers/Binary-embeddings":{"id":"Machine-learning/Multiclass-with-binary-classifiers/Binary-embeddings","title":"\u041a\u043e\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0441 \u0438\u0441\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435\u043c \u043e\u0448\u0438\u0431\u043e\u043a","description":"\u041c\u0435\u0442\u043e\u0434 \u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0441 \u0438\u0441\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435\u043c \u043e\u0448\u0438\u0431\u043e\u043a (error-correcting output codes) \u0434\u043b\u044f \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u043c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043d\u0430\u0431\u043e\u0440\u0430 \u0431\u0438\u043d\u0430\u0440\u043d\u044b\u0445 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0442\u043e\u0440\u043e\u0432. \u0418\u0434\u0435\u0438 \u0443\u0442\u043e\u0447\u043d\u0435\u043d\u0438\u044f \u043c\u0435\u0442\u043e\u0434\u0430.","sidebar":"Machine-learning"},"Machine-learning/Multiclass-with-binary-classifiers/One-vs-all":{"id":"Machine-learning/Multiclass-with-binary-classifiers/One-vs-all","title":"\u041c\u0435\u0442\u043e\u0434 \u043e\u0434\u0438\u043d-\u043f\u0440\u043e\u0442\u0438\u0432-\u0432\u0441\u0435\u0445","description":"\u041c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u0430\u044f \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u044f \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043d\u0430\u0431\u043e\u0440\u0430 \u0431\u0438\u043d\u0430\u0440\u043d\u044b\u0445 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0442\u043e\u0440\u043e\u0432 \u043c\u0435\u0442\u043e\u0434\u043e\u043c \u043e\u0434\u0438\u043d-\u043f\u0440\u043e\u0442\u0438\u0432-\u0432\u0441\u0435\u0445 (one-vs-all, one-vs-rest).","sidebar":"Machine-learning"},"Machine-learning/Multiclass-with-binary-classifiers/One-vs-one":{"id":"Machine-learning/Multiclass-with-binary-classifiers/One-vs-one","title":"\u041c\u0435\u0442\u043e\u0434 \u043e\u0434\u0438\u043d-\u043f\u0440\u043e\u0442\u0438\u0432-\u043e\u0434\u043d\u043e\u0433\u043e","description":"\u041c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u0430\u044f \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u044f \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043d\u0430\u0431\u043e\u0440\u0430 \u0431\u0438\u043d\u0430\u0440\u043d\u044b\u0445 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0442\u043e\u0440\u043e\u0432 \u043c\u0435\u0442\u043e\u0434\u043e\u043c \u043e\u0434\u0438\u043d-\u043f\u0440\u043e\u0442\u0438\u0432-\u043e\u0434\u043d\u043e\u0433\u043e (one-vs-one).","sidebar":"Machine-learning"},"Machine-learning/Numerical-optimization/Gradient-descent":{"id":"Machine-learning/Numerical-optimization/Gradient-descent","title":"\u041c\u0435\u0442\u043e\u0434 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0441\u043f\u0443\u0441\u043a\u0430","description":"\u041c\u0435\u0442\u043e\u0434 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0441\u043f\u0443\u0441\u043a\u0430 (gradient descent) \u0434\u043b\u044f \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u043e\u0432 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u0423\u0441\u043b\u043e\u0432\u0438\u044f \u043e\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0438, \u043e\u0441\u043e\u0431\u0435\u043d\u043d\u043e\u0441\u0442\u0438 \u0440\u0435\u0448\u0435\u043d\u0438\u0439, \u0432\u044b\u0431\u043e\u0440 \u0448\u0430\u0433\u0430 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f (learning rate).","sidebar":"Machine-learning"},"Machine-learning/Numerical-optimization/Gradient-optimization":{"id":"Machine-learning/Numerical-optimization/Gradient-optimization","title":"\u0427\u0438\u0441\u043b\u0435\u043d\u043d\u044b\u0435 \u043c\u0435\u0442\u043e\u0434\u044b \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438","description":"\u0427\u0438\u0441\u043b\u0435\u043d\u043d\u044b\u0435 \u043c\u0435\u0442\u043e\u0434\u044b \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 \u0434\u043b\u044f \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u043e\u0432 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u041f\u043e\u043d\u044f\u0442\u0438\u0435 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u0430 \u0438 \u0430\u043d\u0442\u0438\u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u0430. \u0411\u0435\u0437\u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u044b\u0435 \u043c\u0435\u0442\u043e\u0434\u044b \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Numerical-optimization/Momentum-Nesterov":{"id":"Machine-learning/Numerical-optimization/Momentum-Nesterov","title":"\u0421\u0442\u043e\u0445\u0430\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u044b\u0439 \u0441\u043f\u0443\u0441\u043a \u0441 \u0438\u043d\u0435\u0440\u0446\u0438\u0435\u0439","description":"\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u0438\u043d\u0435\u0440\u0446\u0438\u0438 (momentum) \u0434\u043b\u044f \u0443\u0441\u043a\u043e\u0440\u0435\u043d\u0438\u044f \u043c\u0435\u0442\u043e\u0434\u0430 \u0441\u0442\u043e\u0445\u0430\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0441\u043f\u0443\u0441\u043a\u0430. \u0418\u043d\u0435\u0440\u0446\u0438\u044f \u041d\u0435\u0441\u0442\u0435\u0440\u043e\u0432\u0430 (Nestrov momentum).","sidebar":"Machine-learning"}
1,"Machine-learning/Numerical-optimization/Monitoring":{"id":"Machine-learning/Numerical-optimization/Monitoring","title":"\u041c\u043e\u043d\u0438\u0442\u043e\u0440\u0438\u043d\u0433 \u0441\u0445\u043e\u0434\u0438\u043c\u043e\u0441\u0442\u0438","description":"\u041c\u043e\u043d\u0438\u0442\u043e\u0440\u0438\u043d\u0433 \u0441\u0445\u043e\u0434\u0438\u043c\u043e\u0441\u0442\u0438 \u043c\u0435\u0442\u043e\u0434\u043e\u0432 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438. \u042d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e\u0435 \u0441\u0433\u043b\u0430\u0436\u0438\u0432\u0430\u043d\u0438\u0435 \u0438 \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435.","sidebar":"Machine-learning"},"Machine-learning/Numerical-optimization/Newton-method":{"id":"Machine-learning/Numerical-optimization/Newton-method","title":"\u041c\u0435\u0442\u043e\u0434 \u041d\u044c\u044e\u0442\u043e\u043d\u0430","description":"\u041c\u0435\u0442\u043e\u0434 \u041d\u044c\u044e\u0442\u043e\u043d\u0430 \u0434\u043b\u044f \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u043e\u0432 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u041e\u0431\u043e\u0441\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u0430, \u0435\u0433\u043e \u0434\u043e\u0441\u0442\u043e\u0438\u043d\u0441\u0442\u0432\u0430 \u0438 \u043d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043a\u0438. \u
1041c\u0435\u0442\u043e\u0434\u044b \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 \u0432\u0442\u043e\u0440\u043e\u0433\u043e \u043f\u043e\u0440\u044f\u0434\u043a\u0430.","sidebar":"Machine-learning"},"Machine-learning/Numerical-optimization/Questions":{"id":"Machine-learning/Numerical-optimization/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u044b\u043c \u043c\u0435\u0442\u043e\u0434\u0430\u043c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Numerical-optimization/SGD":{"id":"Machine-learning/Numerical-optimization/SGD","title":"\u041c\u0435\u0442\u043e\u0434 \u0441\u0442\u043e\u0445\u0430\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0441\u043f\u0443\u0441\u043a\u0430","description":"\u041c\u0435\u0442\u043e\u0434 \u0441\u0442\u043e\u0445\u0430\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0441\u043f\u0443\u0441\u043a\u0430 (stochastic gradient descent, SGD) \u0434\u043b\u044f \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u043e\u0432 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u041c\u0438\u043d\u0438\u0431\u0430\u0442\u0447 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432, \u0432\u044b\u0431\u043e\u0440 \u0440\u0430\u0437\u043c\u0435\u0440\u0430 \u043c\u0438\u043d\u0438\u0431\u0430\u0442\u0447\u0430.","sidebar":"Machine-learning"},"Machine-learning/Regression-evaluation/Questions":{"id":"Machine-learning/Regression-evaluation/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438 \u043f\u043e \u0437\u0430\u0434\u0430\u0447\u0435 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Regression-evaluation/Real-vs-approximate-measures":{"id":"Machine-learning/Regression-evaluation/Real-vs-approximate-measures","title":"\u041a\u043e\u043d\u0435\u0447\u043d\u044b\u0435 \u043c\u0435\u0440\u044b \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u0438","description":"\u041a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u0442\u0435\u043b\u0438 \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u0438 (key performance indicators, KPI) \u0438 \u0438\u0445 \u0441\u0432\u044f\u0437\u044c \u0441\u043e \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u044b\u043c\u0438 \u043c\u0435\u0440\u0430\u043c\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Regression-evaluation/Regression-evaluation-metrics":{"id":"Machine-learning/Regression-evaluation/Regression-evaluation-metrics","title":"\u041c\u0435\u0440\u044b \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u044b\u0445 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432","description":"\u0421\u043f\u043e\u0441\u043e\u0431\u044b \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u044b\u0445 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0438 \u0438\u0445 \u0441\u0440\u0430\u0432\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0439 \u0430\u043d\u0430\u043b\u0438\u0437.","sidebar":"Machine-learning"},"Machine-learning/Regression-evaluation/Regression-true-predicted-plot":{"i
1d":"Machine-learning/Regression-evaluation/Regression-true-predicted-plot","title":"\u041f\u043e\u0442\u043e\u0447\u0435\u0447\u043d\u044b\u0439 \u0433\u0440\u0430\u0444\u0438\u043a","description":"\u0412\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0438 \u0430\u043d\u0430\u043b\u0438\u0437 \u043e\u0448\u0438\u0431\u043e\u043a \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0432 \u0437\u0430\u0434\u0430\u0447\u0435 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Simple-models-interpretation/Decision-tree":{"id":"Machine-learning/Simple-models-interpretation/Decision-tree","title":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430","description":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0438 \u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0440\u0435\u0448\u0430\u044e\u0449\u0435\u0433\u043e \u0434\u0435\u0440\u0435\u0432\u0430.","sidebar":"Machine-learning"},"Machine-learning/Simple-models-interpretation/Interpretable-machine-learning":{"id":"Machine-learning/Simple-models-interpretation/Interpretable-machine-learning","title":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u0443\u0435\u043c\u043e\u0435 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435","description":"\u041f\u043e\u043d\u044f\u0442\u0438\u0435 \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u0443\u0435\u043c\u043e\u0441\u0442\u0438 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u0413\u043b\u043e\u0431\u0430\u043b\u044c\u043d\u0430\u044f \u0438 \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u0430\u044f \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u0443\u0435\u043c\u043e\u0441\u0442\u044c. \u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u0443\u0435\u043c\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438 (white-box models) \u0438 \u043d\u0435\u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u0443\u0435\u043c\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438 (black-box models), \u0441\u0446\u0435\u043d\u0430\u0440\u0438\u0438 \u0438\u0445 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"},"Machine-learning/Simple-models-interpretation/Linear-regression":{"id":"Machine-learning/Simple-models-interpretation/Linear-regression","title":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438","description":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u0432\u0435\u0441\u043e\u0432 \u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Simple-models-interpretation/Logistic-regression":{"id":"Machine-learning/Simple-models-interpretation/Logistic-regression","title":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043b\u043e\u0433\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438","description":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u0432\u0435\u0441\u043e\u0432 \u043b\u043e\u0433\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438.","sidebar":"Machine-learning"},"Machine-learning/Simple-models-interpretation/Metric-methods-interpretability":{"id":"Machine-learning/Simple-models-interpretation/Metric-methods-interpretability","title":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u0435\u0442\u043e\u0434\u043e\u0432","description":"\u0418\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u043c\u0435\u0442\u043e\u0434\u0430 K \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0441\u043e\u0441\u0435\u0434\u0435\u0439 \u0438 \u043c\u0435\u0442\u043e\u0434\u0430 \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0438\u0445 \u0446\u0435\u043d\u0442\u0440\u043e\u0438\u0434\u043e\u0432.","sidebar":"Machine-learning"},"Machine-learning/Simple-models-interpretation/Naive-Bayes":{"id":"Machine-learning/Simple-models-interpretation/Naive-Bayes","title":"\u041c\u0435\u0442\u043e\u0434 \u043d\u0430\u0438\u0432\u043d\u043e\u0433\u043e \u0411\u0430\u0439\u0435\u0441\u0430","description":"\u041e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 \u0438 \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0438\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u043c\u0435\u0442\u043e\u0434\u0430 \u043d\u0430\u0438\u0432\u043d\u043e\u0433\u043e \u0411\u0430\u0439\u0435\u0441\u0430. \u041f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u0438\u0435 \u043d\u0430\u0438\u0432\u043d\u043e\u0433\u043e \u0411\u0430\u0439\u0435\u0441\u0430 (naive Bayes assumption).","sidebar":"Machine-learning"},"Machine-learning/Simple-models-interpretation/Questions":{"id":"Machine-learning/Simple-models-interpretation/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u0443\u0435\u043c\u043e\u0441\u0442\u0438 \u043f\u0440\u043e\u0441\u0442\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Machine-learning"}
1,"Machine-learning/whats-next":{"id":"Machine-learning/whats-next","title":"\u0417\u0430\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0435","description":"\u0417\u0430\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0435 \u043a\u043d\u0438\u0433\u0438, \u0440\u0435\u043a\u043e\u043c\u0435\u043d\u0434\u0430\u0446\u0438\u0438 \u043f\u043e \u0437\u0430\u043a\u0440\u0435\u043f\u043b\u0435\u043d\u0438\u044e \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043d\u0430\u0432\u044b\u043a\u043e\u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u0410\u043d\u043e\u043d\u0441 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u0439 \u043a\u043d\u0438\u0433\u0438 \u043f\u043e \u0433\u043b\u0443\u0431\u043e\u043a\u043e\u043c\u0443 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044e (deep learning) \u0438 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0432\u044b\u043c \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u044f\u043c.","sidebar":"Machine-learning"},"Neural-networks/Autoregressive-language-models/Greedy-and-beam-search":{"id":"Neural-networks/Autoregressive-language-models/Greedy-and-beam-search","title":"\u0416\u0430\u0434\u043d\u044b\u0439 \u0438 \u043b\u0443\u0447\u0435\u0432\u043e\u0439 \u043f\u043e\u0438\u0441\u043a","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0436\u0430\u0434\u043d\u043e\u0433\u043e \u0438 \u043b\u0443\u0447\u0435\u0432\u043e\u0433\u043e \u043f\u043e\u0438\u0441\u043a\u0430 - \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435, \u043f\u0440\u0438\u043c\u0435\u0440 \u0440\u0430\u0431\u043e\u0442\u044b, \u0441\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u0435 \u0438 \u0430\u043d\u0430\u043b\u0438\u0437.","sidebar":"Neural-networks"},"Neural-networks/Autoregressive-language-models/Language-models-intro":{"id":"Neural-networks/Autoregressive-language-models/Language-models-intro","title":"\u0412\u0432\u0435\u0434\u0435\u043d\u0438\u0435","description":"\u0412\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u0432 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438. \u0410\u0432\u0442\u043e\u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u044b\u0435 \u0438 \u043c\u0430\u0441\u043a\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438. \u0421\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f \u044f\u0437\u044b\u043a\u043e\u0432\u0430\u044f \u043c\u043e\u0434\u0435\u043b\u044c.","sidebar":"Neural-networks"},"Neural-networks/book-title":{"id":"Neural-networks/book-title","title":"\u041e\u043d\u043b\u0430\u0439\u043d-\u0443\u0447\u0435\u0431\u043d\u0438\u043a \u043f\u043e \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u044f\u043c (deep learning).","description":"\u041e\u043d\u043b\u0430\u0439\u043d-\u0443\u0447\u0435\u0431\u043d\u0438\u043a \u043f\u043e \u0433\u043b\u0443\u0431\u043e\u043a\u0438\u043c \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u043c \u0441\u0435\u0442\u044f\u043c (\u0433\u043b\u0443\u0431\u043e\u043a\u043e\u0435 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435, deep learning) \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u043a\u0443\u0440\u0441\u0430 \u043d\u0430 \u0412\u041c\u041a \u041c\u0413\u0423.","sidebar":"Neural-networks"},"Neural-networks/conclusion":{"id":"Neural-networks/conclusion","title":"\u0417\u0430\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0435","description":"\u0417\u0430\u043a\u043b\u044e\u0447\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0441\u043b\u043e\u0432\u0430 \u0438 \u0440\u0435\u043a\u043e\u043c\u0435\u043d\u0434\u0430\u0446\u0438\u0438 \u0434\u043b\u044f \u0434\u0430\u043b\u044c\u043d\u0435\u0439\u0448\u0435\u0433\u043e \u0438\u0437\u0443\u0447\u0435\u043d\u0438\u044f \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0439 \u0438 \u0433\u043b\u0443\u0431\u043e\u043a\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Neural-networks"},"Neural-networks/Convolutional-architectures/AlexNet-ZFnet":{"id":"Neural-networks/Convolutional-architectures/AlexNet-ZFnet","title":"\u041c\u043e\u0434\u0435\u043b\u0438 AlexNet \u
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\u0440\u0430\u0437\u043c\u0435\u0440\u043d\u043e\u0441\u0442\u0438 \u044d\u043c\u0431\u0435\u0434\u0434\u0438\u043d\u0433\u043e\u0432 \u0441\u043b\u043e\u0432 \u0438 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043c\u0435\u0442\u043e\u0434\u0430 Latent Semantic Analysis (LSA).","sidebar":"Neural-networks"},"Neural-networks/Embeddings/Paragraph-embeddings":{"id":"Neural-networks/Embeddings/Paragraph-embeddings","title":"\u042d\u043c\u0431\u0435\u0434\u0434\u0438\u043d\u0433\u0438 \u043f\u0430\u0440\u0430\u0433\u0440\u0430\u0444\u043e\u0432","description":"\u0411\u0430\u0437\u043e\u0432\u044b\u0435 \u043c\u0435\u0442\u043e\u0434\u044b \u0434\u043b\u044f \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u044d\u043c\u0431\u0435\u0434\u0434\u0438\u043d\u0433\u043e\u0432 \u043f\u0440\u0435\u0434\u043b\u043e\u0436\u0435\u043d\u0438\u0439, \u043f\u0430\u0440\u0430\u0433\u0440\u0430\u0444\u043e\u0432 \u0438 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\u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f Hierarchical SoftMax \u0438 \u043d\u0435\u0433\u0430\u0442\u0438\u0432\u043d\u043e\u0435 \u0441\u044d\u043c\u043f\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 (negative sampling).","sidebar":"Neural-networks"},"Neural-networks/Embeddings/Word-embeddings":{"id":"Neural-networks/Embeddings/Word-embeddings","title":"\u042d\u043c\u0431\u0435\u0434\u0434\u0438\u043d\u0433\u0438 \u0441\u043b\u043e\u0432","description":"\u0412\u0432\u0435\u0434\u0435\u043d\u0438\u0435, \u0447\u0442\u043e \u0442\u0430\u043a\u043e\u0435 \u044d\u043c\u0431\u0435\u0434\u0434\u0438\u043d\u0433 \u0441\u043b\u043e\u0432, \u0441\u0438\u043c\u0432\u043e\u043b\u043e\u0432 \u0438 \u043b\u044e\u0431\u044b\u0445 \u0434\u0438\u0441\u043a\u0440\u0435\u0442\u043d\u044b\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043f\u0440\u043e\u0441\u0442\u044b\u043c\u0438 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\u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u0430\u0432\u0442\u043e\u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a\u0430 \u0434\u043b\u044f \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u044d\u043c\u0431\u0435\u0434\u0434\u0438\u043d\u0433\u043e\u0432 \u0432\u0435\u0440\u0448\u0438\u043d \u0433\u0440\u0430\u0444\u0430 (node embeddings).","sidebar":"Neural-networks"},"Neural-networks/Graph-processing/Graph-convolutional-networks":{"id":"Neural-networks/Graph-processing/Graph-convolutional-networks","title":"C\u0432\u0451\u0440\u0442\u043e\u0447\u043d\u044b\u0435 \u0433\u0440\u0430\u0444\u043e\u0432\u044b\u0435 \u0441\u0435\u0442\u0438","description":"\u0413\u0440\u0430\u0444\u043e\u0432\u044b\u0435 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0435 \u0441\u0435\u0442\u0438-\u043f\u0440\u0438\u043d\u0446\u0438\u043f \u0440\u0430\u0431\u043e\u0442\u044b, \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u043f\u0435\u0440\u0435\u0434\u0430\u0447\u0438 \u0441\u043e\u043e\u0431\u0449\u0435\u043d\u0438\u0439, \u0441\u0432\u0451\u0440\u0442\u043a\u0438 \u043d\u0430 \u0433\u0440\u0430\u0444\u0430\u0445.","sidebar":"Neural-networks"},"Neural-networks/Graph-processing/Graph-isomorphism":{"id":"Neural-networks/Graph-processing/Graph-isomorphism","title":"\u0418\u0437\u043e\u043c\u043e\u0440\u0444\u0438\u0437\u043c \u0433\u0440\u0430\u0444\u043e\u0432","description":"\u0418\u0437\u043e\u043c\u043e\u0440\u0444\u0438\u0437\u043c \u0433\u0440\u0430\u0444\u043e\u0432-\u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435, \u043f\u0440\u0438\u043c\u0435\u0440\u044b \u0438 \u043f\u0440\u0430\u0432\u0438\u043b\u0430 \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u043c\u0430\u0442\u0440\u0438\u0446\u044b \u0441\u043c\u0435\u0436\u043d\u043e\u0441\u0442\u0438 \u0438 \u043c\u0430\u0442\u0440\u0438\u0446\u044b \u0441\u0442\u043f\u0435\u043d\u0435\u0439 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\u0433\u0440\u0430\u0444\u0430.","sidebar":"Neural-networks"},"Neural-networks/Graph-processing/Literature":{"id":"Neural-networks/Graph-processing/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"","sidebar":"Neural-networks"},"Neural-networks/Graph-processing/Tasks-on-graphs":{"id":"Neural-networks/Graph-processing/Tasks-on-graphs","title":"\u0417\u0430\u0434\u0430\u0447\u0438 \u043d\u0430 \u0433\u0440\u0430\u0444\u0430\u0445","description":"\u0412\u0438\u0434\u044b \u0437\u0430\u0434\u0430\u0447, \u0440\u0435\u0448\u0430\u0435\u043c\u044b\u0445 \u043d\u0430 \u0433\u0440\u0430\u0444\u0430\u0445 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u043c\u0438 \u0441\u0435\u0442\u044f\u043c\u0438. \u
1041f\u0440\u0438\u043c\u0435\u0440\u044b \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u043d\u044b\u0445 \u0437\u0430\u0434\u0430\u0447 \u0438\u0437 \u0440\u0430\u0437\u043d\u044b\u0445 \u043f\u0440\u0435\u0434\u043c\u0435\u0442\u043d\u044b\u0445 \u043e\u0431\u043b\u0430\u0441\u0442\u0435\u0439.","sidebar":"Neural-networks"},"Neural-networks/Graph-processing/Training-graph-networks":{"id":"Neural-networks/Graph-processing/Training-graph-networks","title":"\u041e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u0433\u0440\u0430\u0444\u043e\u0432\u044b\u0445 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0439","description":"\u041e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u0433\u0440\u0430\u0444\u043e\u0432\u044b\u0445 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0439-\u0444\u043e\u0440\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043c\u0438\u043d\u0438\u0431\u0430\u0442\u0447\u0435\u0439, \u0441\u043f\u043e\u0441\u043e\u0431\u044b \u0440\u0435\u0433\u0443\u043b\u044f\u0440\u0438\u0437\u0430\u0446\u0438\u0438.","sidebar":"Neural-networks"},"Neural-networks/Instance-segmentation/Mask-R-CNN":{"id":"Neural-networks/Instance-segmentation/Mask-R-CNN","title":"Mask R-CNN","description":"\u041d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u044c Mask R-CNN \u0434\u043b\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u0438\u043d\u0441\u0442\u0430\u043d\u0441 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 (\u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043d\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0438).","sidebar":"Neural-networks"},"Neural-networks/Instance-segmentation/Problem-statement":{"id":"Neural-networks/Instance-segmentation/Problem-statement","title":"\u0421\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u044f \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432","description":"\u0417\u0430\u0434\u0430\u0447\u0430 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 (\u0438\u043d\u0441\u0442\u0430\u043d\u0441 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u044f, instance segmentation). \u0414\u0432\u0443\u0445\u0441\u0442\u0430\u0434\u0438\u0439\u043d\u044b\u0435 \u0438 \u043e\u0434\u043d\u043e\u0441\u0442\u0430\u0434\u0438\u0439\u043d\u044b\u0435 \u043c\u0435\u0442\u043e\u0434\u044b \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438.","sidebar":"Neural-networks"},"Neural-networks/Instance-segmentation/YOLACT":{"id":"Neural-networks/Instance-segmentation/YOLACT","title":"YOLACT","description":"\u041d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u044c Mask R-CNN \u0434\u043b\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u0438\u043d\u0441\u0442\u0430\u043d\u0441 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 (\u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043d\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0438).","sidebar":"Neural-networks"},"Neural-networks/intro":{"id":"Neural-networks/intro","title":"\u0412\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u0432 \u0433\u043b\u0443\u0431\u043e\u043a\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 (deep learning).","description":"\u0412\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u0432 \u0433\u043b\u0443\u0431\u043e\u043a\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435. \u041e\u0442\u043b\u0438\u0447\u0438\u0435 \u0433\u043b\u0443\u0431\u043e\u043a\u043e\u0433\u043e \u0438 \u043d\u0435\u0433\u043b\u0443\u0431\u043e\u043a\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u0414\u0440\u0430\u0439\u0432\u0435\u0440\u044b \u0440\u0430\u0437\u0432\u0438\u0442\u0438\u044f \u0438 \u044d\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u0432\u043e\u043f\u0440\u043e\u0441\u044b.","sidebar":"Neural-networks"},"Neural-networks/Language-model-evaluation/BLEU-metric":{"id":"Neural-networks/Language-model-evaluation/BLEU-metric","title":"\u041c\u0435\u0440\u0430 BLEU","description":"\u041c\u0435\u0442\u043e\u0434 BLEU \u0434\u043b\u044f \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043f\u0435\u0440\u0435\u0432\u043e\u0434\u0430. \u041c\u043e\u0434\u0438\u0444\u0438\u0446\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u0430\u044f \u0443\u043d\u0438\u0433\u0440\u0430\u043c\u043c\u043d\u0430\u044f \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c, \u0448\u0442\u0440\u0430\u0444 \u0437\u0430 \u043a\u0440\u0430\u0442\u043a\u043e\u0441\u0442\u044c, \u043c\u0438\u043a\u0440\u043e\u0443\u0441\u0440\u0435\u0434\u043d\u0435\u043d\u0438\u0435 \u0438 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u0430 \u0447\u0440\u0435\u0437\u043c\u0435\u0440\u043d\u043e\u0439 \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0438.","sidebar":"Neural-networks"},"Neural-networks/Language-model-evaluation/Likelihood-and-perplexity":{"id":"Neural-networks/Language-model-evaluation/Likelihood-and-perplexity","title":"\u041f\u0440\u0430\u0432\u0434\u043e\u043f\u043e\u0434\u043e\u0431\u0438\u0435 \u0438 \u043f\u0435\u0440\u043f\u043b\u0435\u043a\u0441\u0438\u044f","description":"\u041e\u0446\u0435\u043d\u043a\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043f\u0440\u0430\u0432\u0434\u043e\u043f\u043e\u0434\u043e\u0431\u0438\u044f \u0438 \u043f\u0435\u0440\u043f\u043b\u0435\u043a\u0441\u0438\u0438.","sidebar":"Neural-networks"},"Neural-networks/Language-model-evaluation/LLM-as-a-Judge":{"id":"Neural-networks/Language-model-evaluation/LLM-as-a-Judge","title":"\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0432 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0435 \u0441\u0443\u0434\u0435\u0439","description":"\u041e\u0446\u0435\u043d\u043a\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0438 \u0442\u0435\u043a\u0441\u0442\u043e\u0432 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043f\u043e\u0434\u0445\u043e\u0434\u0430 LLM-as-a-Judge. \u0422\u043e\u0447\u0435\u0447\u043d\u0430\u044f \u043e\u0446\u0435\u043d\u043a\u0430, \u043f\u043e\u043f\u0430\u0440\u043d\u043e\u0435 \u0441\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u0435, \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u044b \u0441\u043c\u0435\u0449\u0435\u043d\u0438\u0439 \u0438 \u0441\u043f\u0435\u0446\u0438\u0430\u043b\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438-\u0441\u0443\u0434\u044c\u0438.","sidebar":"Neural-networks"},"Neural-networks/Language-model-evaluation/METEOR- CIDEr- BERTScore-metrics":{"id":"Neural-networks/Language-model-evaluation/METEOR- CIDEr- BERTScore-metrics","title":"METEOR, CIDEr, BERTScore","description":"\u041c\u0435\u0442\u0440\u0438\u043a\u0438 METEOR, CIDEr \u0438 BERTScore \u0434\u043b\u044f \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439.","sidebar":"Neural-networks"},"Neural-networks/Language-model-evaluation/ROUGE-metric":{"id":"Neural-networks/Language-model-evaluation/ROUGE-metric","title":"\u041c\u0435\u0440\u0430 ROUGE","description":"\u041e\u0446\u0435\u043d\u043a\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0438 \u0442\u0435\u043a\u0441\u0442\u043e\u0432 \u0438 \u0441\u0443\u043c\u043c\u0430\u0440\u0438\u0437\u0430\u0446\u0438\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043c\u0435\u0442\u0440\u0438\u043a\u0438 ROUGE. \u0421\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u0435 ROUGE \u0441 BLEU \u0438 WER.","sidebar":"Neural-networks"},"Neural-networks/Language-model-evaluation/WER-and-CER-metrics":{"id":"Neural-networks/Language-model-evaluation/WER-and-CER-metrics","title":"\u041c\u0435\u0440\u044b WER \u0438 CER","description":"\u041e\u0446\u0435\u043d\u043a\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439: \u043c\u0435\u0442\u0440\u0438\u043a\u0438 Word Error Rate (WER) \u0438 Character Error Rate (CER).","sidebar":"Neural-networks"},"Neural-networks/MLP/Activation-functions":{"id":"Neural-networks/MLP/Activation-functions","title":"\u0424\u0443\u043d\u043a\u0446\u0438\u0438 \u0430\u043a\u0442\u0438\u0432\u0430\u0446\u0438\u0438","description":"\u041e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u0430\u043a\u0442\u0438\u0432\u0430\u0446\u0438\u0438 \u0432 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u044f\u0445. \u041e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u044f, \u0433\u0440\u0430\u0444\u0438\u043a\u0438, \u043f\u0440\u0438\u043c\u0435\u0440\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0438 \u043e\u0442\u043b\u0438\u0447\u0438\u044f \u043d\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u043c \u0443\u0440\u043e\u0432\u043d\u0435.","sidebar":"Neural-networks"},"Neural-networks/MLP/Modeling-ability":{"id":"Neural-networks/MLP/Modeling-ability","title":"\u041c\u043e\u0434\u0435\u043b\u0438\u0440\u0443\u044e\u0449\u0438\u0435 \u0441\u043f\u043e\u0441\u043e\u0431\u043d\u043e\u0441\u0442\u0438 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438","description":"\u041c\u0438\u043d\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0435 \u0447\u0438\u0441\u043b\u043e \u0441\u043b\u043e\u0451\u0432 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u043e\u0439 \u0441\u0435\u0442\u0438 \u0434\u043b\u044f \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438 \u0438 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438. \u
1041c\u043e\u0442\u0438\u0432\u0430\u0446\u0438\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0433\u043b\u0443\u0431\u043e\u043a\u0438\u0445 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439 \u0441 \u0431\u043e\u043b\u044c\u0448\u0438\u043c \u0447\u0438\u0441\u043b\u043e\u043c \u0441\u043b\u043e\u0451\u0432.","sidebar":"Neural-networks"},"Neural-networks/MLP/Multilayer-perceptron":{"id":"Neural-networks/MLP/Multilayer-perceptron","title":"\u041c\u043d\u043e\u0433\u043e\u0441\u043b\u043e\u0439\u043d\u044b\u0439 \u043f\u0435\u0440\u0441\u0435\u043f\u0442\u0440\u043e\u043d","description":"\u041e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 \u0438 \u043f\u0440\u0438\u043c\u0435\u0440 \u043c\u043d\u043e\u0433\u043e\u0441\u043b\u043e\u0439\u043d\u043e\u0433\u043e \u043f\u0435\u0440\u0441\u0435\u043f\u0442\u0440\u043e\u043d\u0430, \u043f\u043e\u043b\u043d\u043e\u0441\u0432\u044f\u0437\u043d\u044b\u0435 \u0441\u043b\u043e\u0438, \u0440\u0430\u0441\u0447\u0451\u0442 \u0447\u0438\u0441\u043b\u0430 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u043e\u0432 \u0432 \u043d\u0438\u0445. \u041e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0439.","sidebar":"Neural-networks"},"Neural-networks/MLP/Neuron-model":{"id":"Neural-networks/MLP/Neuron-model","title":"\u041c\u043e\u0434\u0435\u043b\u044c \u043d\u0435\u0439\u0440\u043e\u043d\u0430","description":"\u041c\u043e\u0434\u0435\u043b\u044c \u043d\u0435\u0439\u0440\u043e\u043d\u0430 \u0432 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u044f\u0445. \u0424\u0443\u043d\u043a\u0446\u0438\u0438 \u0430\u043a\u0442\u0438\u0432\u0430\u0446\u0438\u0438 \u0434\u043b\u044f \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u0437\u0430\u0434\u0430\u0447\u0438 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0438 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438.","sidebar":"Neural-networks"},"Neural-networks/MLP/Outputs-loss-functions":{"id":"Neural-networks/MLP/Outputs-loss-functions","title":"\u0412\u044b\u0445\u043e\u0434\u044b \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438 \u0438 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043f\u043e\u0442\u0435\u0440\u044c","description":"\u0412\u044b\u0445\u043e\u0434\u044b \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438 \u0434\u043b\u044f \u0437\u0430\u0434\u0430\u0447 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438, \u0432\u0435\u043a\u0442\u043e\u0440\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438, \u0431\u0438\u043d\u0430\u0440\u043d\u043e\u0439 \u0438 \u043c\u043d\u043e\u0433\u043e\u043a\u043b\u0430\u0441\u0441\u043e\u0432\u043e\u0439 \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u043a\u0430\u0446\u0438\u0438. \u041f\u0440\u0438\u043c\u0435\u0440\u044b \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043f\u043e\u0442\u0435\u0440\u044c \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0441\u043b\u0443\u0447\u0430\u044f.","sidebar":"Neural-networks"},"Neural-networks/MLP/Representation-learning":{"id":"Neural-networks/MLP/Representation-learning","title":"\u041e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0439","description":"\u0417\u0430\u0434\u0430\u0447\u0430 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u043c\u0435\u0436\u0443\u0442\u043e\u0447\u043d\u044b\u0445 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0439 (representation learning) \u0432 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u044f\u0445. \u0413\u0435\u043e\u043c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0441\u043c\u044b\u0441\u043b \u0442\u0430\u043a\u0438\u0445 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0439, \u043f\u0435\u0440\u0435\u0432\u043e\u0434\u044f\u0449\u0438\u0445 \u043e\u0431\u044a\u0435\u043a\u0442\u044b \u043c\u043d\u043e\u0433\u043e\u043c\u0435\u0440\u043d\u043e\u0433\u043e \u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0441\u0442\u0432\u0430 \u0432 \u043c\u0430\u043b\u043e\u043c\u0435\u0440\u043d\u043e\u0435 \u043c\u043d\u043e\u0433\u043e\u043e\u0431\u0440\u0430\u0437\u0438\u0435 (low dimensional manifold). \u041f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u043d\u044b\u0435 \u043f\u0440\u043e\u043c\u0435\u0436\u0443\u0442\u043e\u0447\u043d\u044b\u0435 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u0430\u043a\u0442\u0438\u0432\u0430\u0446\u0438\u0439 \u0433\u043b\u0443\u0431\u043e\u043a\u0438\u0445 \u0441\u043b\u043e\u0451\u0432 \u0441\u0432\u0451\u0440\u0442\u043e\u0447\u043d\u043e\u0439 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u043e\u0439 \u0441\u0435\u0442\u0438.","sidebar":"Neural-networks"},"Neural-networks/MLP/Weights-symmetries":{"id":"Neural-networks/MLP/Weights-symmetries","title":"\u0421\u0438\u043c\u043c\u0435\u0442\u0440\u0438\u044f \u0432 \u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0441\u0442\u0432\u0435 \u0432\u0435\u0441\u043e\u0432","description":"\u041d\u0435\u043e\u0434\u043d\u043e\u0437\u043d\u0430\u0447\u043d\u043e\u0441\u0442\u044c \u043c\u0435\u0436\u0434\u0443 \u043f\u0440\u043e\u0433\u043d\u043e\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u0444\u0443\u043d\u043a\u0446\u0438\u044f\u043c\u0438 \u0438 \u0432\u0435\u0441\u0430\u043c\u0438 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438, \u043c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0441\u0442\u044c \u044d\u043a\u0432\u0438\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u044b\u0445 \u0440\u0435\u0448\u0435\u043d\u0438\u0439.","sidebar":"Neural-networks"},"Neural-networks/Object-detection/CenterNet":{"id":"Neural-networks/Object-detection/CenterNet","title":"\u041c\u043e\u0434\u0435\u043b\u044c CenterNet","description":"\u041c\u043e\u0434\u0435\u043b\u044c CenterNet \u0434\u043b\u044f \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043d\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f\u0445.","sidebar":"Neural-networks"},"Neural-networks/Object-detection/CornerNet":{"id":"Neural-networks/Object-detection/CornerNet","title":"\u041c\u043e\u0434\u0435\u043b\u044c CornerNet","description":"\u041c\u043e\u0434\u0435\u043b\u044c CornerNet \u0434\u043b\u044f \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043d\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0438, \u0441orner pooling.","sidebar":"Neural-networks"},"Neural-networks/Object-detection/Deformable-CNN":{"id":"Neural-networks/Object-detection/Deformable-CNN","title":"\u0414\u0435\u0444\u043e\u0440\u043c\u0438\u0440\u0443\u0435\u043c\u044b\u0435 \u0430\u0440\u0445\u0438\u0442\u0435\u043a\u0442\u0443\u0440\u044b","description":"\u0414\u0435\u0444\u043e\u0440\u043c\u0438\u0440\u0443\u0435\u043c\u0430\u044f \u0441\u0432\u0451\u0440\u0442\u043a\u0430 \u0438 \u0434\u0435\u0444\u043e\u0440\u043c\u0438\u0440\u0443\u0435\u043c\u044b\u0439 ROI \u043f\u0443\u043b\u0438\u043d\u0433 \u0434\u043b\u044f \u0431\u043e\u043b\u0435\u0435 \u043b\u043e\u043a\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u043d\u043d\u043e\u0433\u043e \u0438\u0437\u0432\u043b\u0435\u0447\u0435\u043d\u0438\u044f \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u0440\u0430\u0441\u043f\u043e\u0437\u043d\u0430\u0432\u0430\u0435\u043c\u043e\u0433\u043e \u043e\u0431\u044a\u0435\u043a\u0442\u0430 \u0432 \u0437\u0430\u0434\u0430\u0447\u0430\u0445 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u0438 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438.","sidebar":"Neural-networks"},"Neural-networks/Object-detection/Feature-Pyramid-Network":{"id":"Neural-networks/Object-detection/Feature-Pyramid-Network","title":"\u0421\u0435\u0442\u044c \u043f\u0438\u0440\u0430\u043c\u0438\u0434\u0430\u043b\u044c\u043d\u044b\u0445 \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 (FPN)","description":"\u041c\u0435\u0442\u043e\u0434 feature pyramid network (FPN) \u0434\u043b\u044f \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0433\u043e \u0438\u0437\u0432\u043b\u0435\u0447\u0435\u043d\u0438\u044f \u043f\u0440\u0438\u0437\u043d\u0430\u043a\u043e\u0432 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f \u0438 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432.","sidebar":"Neural-networks"},"Neural-networks/Object-detection/Non-maximum-supression":{"id":"Neural-networks/Object-detection/Non-maximum-supression","title":"\u041f\u043e\u0434\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u043d\u0435\u043c\u0430\u043a\u0441\u0438\u043c\u0443\u043c\u043e\u0432","description":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u043f\u043e\u0434\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u043d\u0435\u043c\u0430\u043a\u0441\u0438\u043c\u0443\u043c\u043e\u0432 (non-maximum supression, NMS) \u0432 \u0437\u0430\u0434\u0430\u0447\u0435 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432. \u0412\u0430\u0440\u0438\u0430\u043d\u0442 \u043c\u044f\u0433\u043a\u043e\u0433\u043e \u043f\u043e\u0434\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u043d\u0435\u043c\u0430\u043a\u0441\u0438\u043c\u0443\u043c\u043e\u0432 (soft-NMS).","sidebar":"Neural-networks"},"Neural-networks/Object-detection/Object-detection-task":{"id":"Neural-networks/Object-detection/Object-detection-task","title":"\u0414\u0435\u0442\u0435\u043a\u0446\u0438\u044f \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432","description":"\u0417\u0430\u0434\u0430\u0447\u0430 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043d\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0438 \u0438 \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u043f\u043e\u0434\u0445\u043e\u0434 \u0434\u043b\u044f \u0435\u0451 \u0440\u0435\u0448\u0435\u043d\u0438\u044f.","sidebar":"Neural-networks"},"Neural-networks/Object-detection/Quality-metrics":{"id":"Neural-networks/Object-detection/Quality-metrics","title":"\u041e\u0446\u0435\u043d\u043a\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043d\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f\u0445.","sidebar":"Neural-networks"},"Neural-networks/Object-detection/Questions":{"id":"Neural-networks/Object-detection/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"","sidebar":"Neural-networks"},"Neural-networks/Object-detection/RetinaNet":{"id":"Neural-networks/Object-detection/RetinaNet","title":"\u041c\u043e\u0434\u0435\u043b\u044c RetinaNet","description":"\u041c\u043e\u0434\u0435\u043b\u044c RetinaNet \u0434\u043b\u044f \u0434\u0435\u0442\u0435\u043a\u0446\u0438\u0438 \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 - \u0430\u0440\u0445\u0438\u0442\u0435\u043a\u0442\u0443\u0440\u0430, \u043d\u0430\u0441\u0442\u0440\u043e\u043a\u0430, \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043f\u043e\u0442\u0435\u0440\u044c, focal loss.","sidebar":"Neural-networks"},"Neural-networks/Object-detection/SSD":{"id":"Neural-networks/Object-detection/SSD","title":"\u041c\u043e\u0434\u0435\u043b\u044c SSD","de
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\u0437\u0430\u0434\u0430\u0447\u0438","description":"\u0422\u0440\u0430\u043d\u0441\u0444\u0435\u0440\u043d\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 (transfer learning) \u043f\u0440\u0438 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0435 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439. \u0412\u0438\u0434\u044b \u0442\u0440\u0430\u043d\u0441\u0444\u0435\u0440\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f.","sidebar":"Neural-networks"},"Neural-networks/Regularization/Weights-regularization":{"id":"Neural-networks/Regularization/Weights-regularization","title":"\u0420\u0435\u0433\u0443\u043b\u044f\u0440\u0438\u0437\u0430\u0446\u0438\u044f \u0432\u0435\u0441\u043e\u0432 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438","description":"\u0420\u0435\u0433\u0443\u043b\u044f\u0440\u0438\u0437\u0430\u0446\u0438\u044f \u0432\u0435\u0441\u043e\u0432 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438 - L1 \u0438 L2 \u0440\u0435\u0433\u0443\u043b\u044f\u0440\u0438\u0437\u0430\u0446\u0438\u044f, \u0444\u043e\u0440\u043c\u0443\u043b\u0430, \u043e\u0442\u043b\u0438\u0447\u0438\u044f.","sidebar":"Neural-networks"},"Neural-networks/Semantic-segmentation/Accounting-for-context":{"id":"Neural-networks/Semantic-segmentation/Accounting-for-context","title":"\u0423\u0447\u0451\u0442 \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442\u0430","description":"\u041d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0432\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438 PSPnet \u0438 DeepLab, \u043f\u043e\u0432\u044b\u0448\u0430\u044e\u0449\u0438\u0435 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u043e \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439 \u0437\u0430 \u0441\u0447\u0451\u0442 \u0443\u0447\u0451\u0442\u0430 \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442\u0430.","sidebar":"Neural-networks"},"Neural-networks/Semantic-segmentation/FCN":{"id":"Neural-networks/Semantic-segmentation/FCN","title":"Fully Convolutional Network","description":"Fully Convolutional Network \u0434\u043b\u044f \u0441\u0435\u043c\u0430\u043d\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439.","sidebar":"Neural-networks"},"Neural-networks/Semantic-segmentation/Questions":{"id":"Neural-networks/Semantic-segmentation/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"","sidebar":"Neural-networks"},"Neural-networks/Semantic-segmentation/Semantic-segmentation-approaches":{"id":"Neural-networks/Semantic-segmentation/Semantic-segmentation-approaches","title":"\u041f\u043e\u0434\u0445\u043e\u0434\u044b \u043a \u0440\u0435\u0448\u0435\u043d\u0438\u044e","description":"\u041f\u0440\u043e\u0441\u0442\u044b\u0435 \u043f\u043e\u0434\u0445\u043e\u0434\u044b \u043a \u0440\u0435\u0448\u0435\u043d\u0438\u044e \u0437\u0430\u0434\u0430\u0447\u0438 \u0441\u0435\u043c\u0430\u043d\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439 \u0438 \u0438\u0445 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u0438\u044f.","sidebar":"Neural-networks"},"Neural-networks/Semantic-segmentation/Semantic-segmentation-quality-metrics":{"id":"Neural-networks/Semantic-segmentation/Semantic-segmentation-quality-metrics","title":"\u041c\u0435\u0440\u044b \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432","description":"\u041c\u0435\u0440\u044b \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043e\u0446\u0435\u043d\u043a\u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0441\u0435\u043c\u0430\u043d\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438.","sidebar":"Neural-networks"},"Neural-networks/Semantic-segmentation/Semantic-segmentation-task":{"id":"Neural-networks/Semantic-segmentation/Semantic-segmentation-task","title":"\u0421\u0435\u043c\u0430\u043d\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u044f","description":"\u0417\u0430\u0434\u0430\u0447\u0430 \u0441\u0435\u043c\u0430\u043d\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439.","sidebar":"Neural-networks"},"Neural-networks/Semantic-segmentation/U-net-and-extensions":{"id":"Neural-networks/Semantic-segmentation/U-net-and-extensions","title":"\u041c\u043e\u0434\u0435\u043b\u044c U-net \u0438 \u0435\u0451 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u044b","description":"\u041c\u043e\u0434\u0435\u043b\u044c U-net \u0434\u043b\u044f \u0441\u0435\u043c\u0430\u043d\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0441\u0435\u0433\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u0438 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439 \u0438 \u0435\u0451 \u0440\u0430\u0437\u0432\u0438\u0442\u0438\u0435.","sidebar":"Neural-networks"},"Neural-networks/Semantic-segmentation/Upsampling-operations":{"id":"Neural-networks/Semantic-segmentation/Upsampling-operations","title":"\u041f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u0435 \u0440\u0430\u0437\u0440\u0435\u0448\u0435\u043d\u0438\u044f","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u043f\u043e\u0432\u044b\u0448\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u0440\u0430\u0437\u0440\u0435\u0448\u0435\u043d\u0438\u044f (upsampling) \u043f\u0440\u0438 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0432\u043e\u0439 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0435 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439.","sidebar":"Neural-networks"},"Neural-networks/Special-architectures/Autoencoders":{"id":"Neural-networks/Special-architectures/Autoencoders","title":"\u0410\u0432\u0442\u043e\u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a","description":"\u0410\u0440\u0445\u0438\u0442\u0435\u043a\u0442\u0443\u0440\u0430 \u0430\u0432\u0442\u043e\u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a\u0430 \u0432 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u044f\u0445, \u0434\u043b\u044f \u0447\u0435\u0433\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442\u0441\u044f \u0430\u0432\u0442\u043e\u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a\u0438, \u0432\u0438\u0434\u044b \u0430\u0432\u0442\u043e\u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a\u043e\u0432.","sidebar":"Neural-networks"},"Neural-networks/Special-architectures/Contrastive-learning":{"id":"Neural-networks/Special-architectures/Contrastive-learning","title":"\u041a\u043e\u043d\u0442\u0440\u0430\u0441\u0442\u043d\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435","description":"\u041a\u043e\u043d\u0442\u0440\u0430\u0441\u0442\u043d\u043e\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0441\u0438\u0430\u043c\u0441\u043a\u0438\u0445 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439 - \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435, \u0440\u0435\u0448\u0430\u0435\u043c\u044b\u0435 \u0437\u0430\u0434\u0430\u0447\u0438, \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043f\u043e\u0442\u0435\u0440\u044c, \u043f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430 \u0430\u0440\u0445\u0438\u0442\u0435\u043a\u0442\u0443\u0440\u044b.","sidebar":"Neural-networks"},"Neural-networks/Special-architectures/HyperNet":{"id":"Neural-networks/Special-architectures/HyperNet","title":"\u0413\u0438\u043f\u0435\u0440\u0441\u0435\u0442\u044c","de
1scription":"\u0410\u0440\u0445\u0438\u0442\u0435\u043a\u0442\u0443\u0440\u0430 \u0433\u0438\u043f\u0435\u0440\u0441\u0435\u0442\u0438 (hypernetwork) - \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435, \u0441\u0445\u0435\u043c\u0430, \u0434\u043e\u0441\u0442\u043e\u0438\u043d\u0441\u0442\u0432\u0430, \u043c\u043e\u0442\u0438\u0432\u0430\u0446\u0438\u044f \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f.","sidebar":"Neural-networks"},"Neural-networks/Special-architectures/Questions":{"id":"Neural-networks/Special-architectures/Questions","title":"\u0412\u043e\u043f\u0440\u043e\u0441\u044b \u0434\u043b\u044f \u0441\u0430\u043c\u043e\u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0438","description":"","sidebar":"Neural-networks"},"Neural-networks/Special-architectures/RBF-networks":{"id":"Neural-networks/Special-architectures/RBF-networks","title":"\u0421\u0435\u0442\u044c \u0440\u0430\u0434\u0438\u0430\u043b\u044c\u043d\u044b\u0445 \u0431\u0430\u0437\u0438\u0441\u043d\u044b\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439","description":"\u0421\u0435\u0442\u044c \u0440\u0430\u0434\u0438\u0430\u043b\u044c\u043d\u044b\u0445 \u0431\u0430\u0437\u0438\u0441\u043d\u044b\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439.","sidebar":"Neural-networks"},"Neural-networks/Tasks/Custom-learning-tasks":{"id":"Neural-networks/Tasks/Custom-learning-tasks","title":"\u0421\u043f\u0435\u0446\u0438\u0430\u043b\u044c\u043d\u044b\u0435 \u0442\u0438\u043f\u044b \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439","description":"\u0422\u0438\u043f\u044b \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0439.","sidebar":"Neural-networks"},"Neural-networks/Tasks/Graph-task-examples":{"id":"Neural-networks/Tasks/Graph-task-examples","title":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0433\u0440\u0430\u0444\u043e\u0432","description":"\u0417\u0430\u0434\u0430\u0447\u0438 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0433\u0440\u0430\u0444\u043e\u0432. \u0414\u0430\u043d\u043d\u044b\u0435, \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043c\u044b\u0435 \u0432 \u0432\u0438\u0434\u0435 \u0433\u0440\u0430\u0444\u043e\u0432.","sidebar":"Neural-networks"},"Neural-networks/Tasks/Image-task-examples":{"id":"Neural-networks/Tasks/Image-task-examples","title":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439","description":"\u0417\u0430\u0434\u0430\u0447\u0438 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439 \u043f\u0440\u0438 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0435 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439.","sidebar":"Neural-networks"},"Neural-networks/Tasks/Other-domains":{"id":"Neural-networks/Tasks/Other-domains","title":"\u0414\u0440\u0443\u0433\u0438\u0435 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f","description":"\u041f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439 \u0434\u043b\u044f \u0440\u0430\u0437\u043d\u044b\u0445 \u0442\u0438\u043f\u043e\u0432 \u0434\u0430\u043d\u043d\u044b\u0445.","sidebar":"Neural-networks"},"Neural-networks/Tasks/Sound-task-examples":{"id":"Neural-networks/Tasks/Sound-task-examples","title":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0437\u0432\u0443\u043a\u0430","description":"\u0417\u0430\u0434\u0430\u0447\u0438 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0438 \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0438 \u0437\u0432\u0443\u043a\u043e\u0432. \u0421\u043f\u043e\u0441\u043e\u0431\u044b \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u0437\u0432\u0443\u043a\u0430.","sidebar":"Neural-networks"},"Neural-networks/Tasks/Text-task-examples":{"id":"Neural-networks/Tasks/Text-task-examples","title":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0442\u0435\u043a\u0441\u0442\u0430","description":"\u0417\u0430\u0434\u0430\u0447\u0438 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0442\u0435\u043a\u0441\u0442\u043e\u0432.","sidebar":"Neural-networks"},"Neural-networks/Tasks/Video-task-examples":{"id":"Neural-networks/Tasks/Video-task-examples","title":"\u041e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0432\u0438\u0434\u0435\u043e","description":"\u0417\u0430\u0434\u0430\u0447\u0438 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0438 \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0438 \u0432\u0438\u0434\u0435\u043e\u0434\u0430\u043d\u043d\u044b\u0445. \u041d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0432\u0430\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0432\u0438\u0434\u0435\u043e \u0434\u0430\u043d\u043d\u044b\u0445.","sidebar":"Neural-networks"},"Neural-networks/Text-tokenization-methods/BBPE-tokenizer":{"id":"Neural-networks/Text-tokenization-methods/BBPE-tokenizer","title":"Byte-Level BPE \u0438 Tiktoken","description":"\u0422\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u044f \u043d\u0430 \u0443\u0440\u043e\u0432\u043d\u0435 \u0431\u0430\u0439\u0442\u043e\u0432 (Byte-Level BPE) \u0438 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0430 Tiktoken. \u0420\u0435\u0448\u0435\u043d\u0438\u0435 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u044b \u043d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u044b\u0445 \u0441\u043b\u043e\u0432 (OOV) \u0438 \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u044f \u0441\u043b\u043e\u0432\u0430\u0440\u0435\u0439 \u0434\u043b\u044f \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439.","sidebar":"Neural-networks"},"Neural-networks/Text-tokenization-methods/BPE-tokenizer":{"id":"Neural-networks/Text-tokenization-methods/BPE-tokenizer","title":"\u0422\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0442\u043e\u0440 BPE","de
1scription":"\u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u0438 BPE (Byte-Pair Encoding). \u041e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 BPE, \u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0438 \u0434\u0435\u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435. \u041f\u0440\u0435-\u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u044f \u0442\u0435\u043a\u0441\u0442\u0430 \u0438 \u0440\u0435\u0448\u0435\u043d\u0438\u0435 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u044b \u0440\u0430\u0437\u0434\u0435\u043b\u0435\u043d\u0438\u044f \u0441\u043b\u043e\u0432. \u041f\u0435\u0440\u0435\u0445\u043e\u0434 \u043a Byte-Level BPE.","sidebar":"Neural-networks"},"Neural-networks/Text-tokenization-methods/SentencePiece-tokenizer":{"id":"Neural-networks/Text-tokenization-methods/SentencePiece-tokenizer","title":"\u0422\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0442\u043e\u0440 SentencePiece","description":"\u0422\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0442\u043e\u0440 SentencePiece \u0438 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c Unigram. \u041f\u0440\u043e\u0431\u043b\u0435\u043c\u0430 \u0434\u0435\u0442\u0435\u0440\u043c\u0438\u043d\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u0438, \u0432\u0435\u0440\u043e\u044f\u0442\u043d\u043e\u0441\u0442\u043d\u043e\u0435 \u0441\u044d\u043c\u043f\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043f\u043e\u0434\u0441\u043b\u043e\u0432 \u0438 \u0441\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u0435 \u0441 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0430\u043c\u0438 \u0442\u0438\u043f\u0430 BPE.","sidebar":"Neural-networks"},"Neural-networks/Text-tokenization-methods/Text-tokenization":{"id":"Neural-networks/Text-tokenization-methods/Text-tokenization","title":"\u0422\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u044f \u0442\u0435\u043a\u0441\u0442\u0430","description":"\u0422\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u044f \u0442\u0435\u043a\u0441\u0442\u0430 \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438. \u041f\u043e\u0441\u043b\u043e\u0432\u043d\u0430\u044f, \u043f\u043e\u0441\u0438\u043c\u0432\u043e\u043b\u044c\u043d\u0430\u044f \u0438 \u0441\u0430\u0431\u0432\u043e\u0440\u0434-\u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u044f. \u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u044b BPE, Byte-level BPE, WordPiece \u0438 SentencePiece. \u041d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0442\u0435\u043a\u0441\u0442\u0430.","sidebar":"Neural-networks"},"Neural-networks/Text-tokenization-methods/WordPiece-tokenizer":{"id":"Neural-networks/Text-tokenization-methods/WordPiece-tokenizer","title":"\u0422\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0442\u043e\u0440 WordPiece","description":"\u0422\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0442\u043e\u0440 WordPiece \u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0438. \u0410\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043c\u0430\u043a\u0441\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 \u043f\u0440\u0430\u0432\u0434\u043e\u043f\u043e\u0434\u043e\u0431\u0438\u044f, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043c\u0430\u0440\u043a\u0435\u0440\u0430 \u043f\u0440\u043e\u0434\u043e\u043b\u0436\u0435\u043d\u0438\u044f \u0441\u043b\u043e\u0432\u0430, \u043f\u0440\u043e\u0446\u0435\u0441\u0441 \u0438\u043d\u0444\u0435\u0440\u0435\u043d\u0441\u0430 (MaxMatch) \u0438 \u0430\u043d\u0430\u043b\u0438\u0437 \u043c\u0435\u0442\u043e\u0434\u0430.","sidebar":"Neural-networks"},"Neural-networks/Training-simplification/BatchNorm":{"id":"Neural-networks/Training-simplification/BatchNorm","title":"\u0411\u0430\u0442\u0447-\u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f","description":"\u0411\u0430\u0442\u0447-\u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u043e\u0439 \u0441\u0435\u0442\u0438 - \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435, \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0435, \u043b\u043e\u0433\u0438\u043a\u0430 \u0440\u0430\u0431\u043e\u0442\u044b \u0432 \u0440\u0435\u0436\u0438\u043c\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0438 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u0441\u0435\u0442\u0438.","sidebar":"Neural-networks"},"Neural-networks/Training-simplification/Gradient-clipping":{"id":"Neural-networks/Training-simplification/Gradient-clipping","title":"\u041e\u0431\u0440\u0435\u0437\u043a\u0430 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u0430","description":"\u041e\u0431\u0440\u0435\u0437\u043a\u0430 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u0430 (gradient clipping) \u0438 \u0430\u0434\u0430\u043f\u0442\u0438\u0432\u043d\u0430\u044f \u043e\u0431\u0440\u0435\u0437\u043a\u0430 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u0430 (adaptive gradient clipping) \u0432 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u044f\u0445.","sidebar":"Neural-networks"}
1,"Neural-networks/Training-simplification/LayerNorm":{"id":"Neural-networks/Training-simplification/LayerNorm","title":"\u041d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0441\u043b\u043e\u044f","description":"\u041d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u0441\u043b\u043e\u044f (layer normalization, layer norm) \u0432 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u044f\u0445 - \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435, \u043c\u043e\u0442\u0438\u0432\u0430\u0446\u0438\u044f, \u043f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430, \u0441\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u0435 \u0441 \u0431\u0430\u0442\u0447-\u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0435\u0439.","sidebar":"Neural-networks"},"Neural-networks/Training-simplification/ResBlock":{"id":"Neural-networks/Training-simplification/ResBlock","title":"\u041e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u044b\u0439 \u0431\u043b\u043e\u043a","description":"\u041e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u044b\u0439 \u0431\u043b\u043e\u043a (residual block) \u0438 \u043e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u0430\u044f \u0441\u0435\u0442\u044c (residual net, ResNet) \u0434\u043b\u044f \u0431\u043e\u043b\u0435\u0435 \u0431\u044b\u0441\u0442\u0440\u043e\u0439 \u0438 \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0439 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438.","sidebar":"Neural-networks"},"Neural-networks/Training/Backpropagation":{"id":"Neural-networks/Training/Backpropagation","title":"\u0410\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u0434\u0438\u0444\u0444\u0435\u0440\u0435\u043d\u0446\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435","description":"\u041c\u0435\u0442\u043e\u0434 \u043e\u0431\u0440\u0430\u0442\u043d\u043e\u0433\u043e \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u043e\u0448\u0438\u0431\u043a\u0438 (backpropagation, backprop), \u043f\u0440\u0438\u043c\u0435\u0440 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u0438 \u0435\u0433\u043e \u0430\u043b\u044c\u0442\u0435\u0440\u043d\u0430\u0442\u0438\u0432\u044b \u0434\u043b\u044f \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u044f \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043e\u0432 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u043f\u043e\u0442\u0435\u0440\u044c \u043f\u0440\u0438 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0435 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439.","sidebar":"Neural-networks"},"Neural-networks/Training/Initialization":{"id":"Neural-networks/Training/Initialization","title":"\u0418\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u0438\u043d\u0438\u0446\u0438\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0432\u0435\u0441\u043e\u0432 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438 \u043f\u0435\u0440\u0435\u0434 \u0435\u0451 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u043e\u0439. \u0421\u0432\u0439\u043e\u0441\u0442\u0432\u0430 \u0441\u043e\u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u0434\u0438\u0441\u043f\u0440\u0435\u0441\u0438\u0438 \u0430\u043a\u0442\u0438\u0432\u0430\u0446\u0438\u0439 \u0438 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043e\u0432 \u043f\u043e \u0441\u043b\u043e\u044f\u043c \u0441\u0435\u0442\u0438.","sidebar":"Neural-networks"}
1,"Neural-networks/Training/Learning-rate-scheduling":{"id":"Neural-networks/Training/Learning-rate-scheduling","title":"\u0412\u044b\u0431\u043e\u0440 \u0448\u0430\u0433\u0430 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u0443\u043c\u0435\u043d\u044c\u0448\u0435\u043d\u0438\u044f \u0448\u0430\u0433\u0430 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f (learning rate scheduling) \u043f\u043e \u0445\u043e\u0434\u0443 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0438.","sidebar":"Neural-networks"},"Neural-networks/Training/Opt-methods-fixed-lr":{"id":"Neural-networks/Training/Opt-methods-fixed-lr","title":"\u041e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u044b \u0441 \u043f\u043e\u0441\u0442\u043e\u044f\u043d\u043d\u044b\u043c \u0448\u0430\u0433\u043e\u043c","description":"\u0411\u0430\u0437\u043e\u0432\u044b\u0435 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u044b\u0435 \u043c\u0435\u0442\u043e\u0434\u044b \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0439 - \u043c\u0435\u0442\u043e\u0434 \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0441\u043f\u0443\u0441\u043a\u0430, \u0441\u0442\u043e\u0445\u0430\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0433\u0440\u0430\u0434\u0438\u0435\u043d\u0442\u043d\u043e\u0433\u043e \u0441\u043f\u0443\u0441\u043a\u0430, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u0438\u043d\u0435\u0440\u0446\u0438\u0438 \u0438 \u0438\u043d\u0435\u0440\u0446\u0438\u0438 \u041d\u0435\u0441\u0442\u0435\u0440\u043e\u0432\u0430.","sidebar":"Neural-networks"},"Neural-networks/Training/Opt-methods-variable-lr":{"id":"Neural-networks/Training/Opt-methods-variable-lr","title":"\u041e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0442\u043e\u0440\u044b \u0441 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u043c \u0448\u0430\u0433\u043e\u043c","description":"\u041c\u0435\u0442\u043e\u0434\u044b \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 \u0434\u043b\u044f \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0439 - AdaGrad, RMSprop, Adam. \u0418\u0445 \u0438\u0434\u0435\u044f - \u0430\u0434\u0430\u043f\u0442\u0438\u0432\u043d\u043e\u0435 \u0438\u0437\u043c\u0435\u043d\u0435\u043d\u0438\u0435 \u0448\u0430\u0433\u0430 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0432\u0434\u043e\u043b\u044c \u043a\u0430\u0436\u0434\u043e\u0439 \u043e\u0441\u0438.","sidebar":"Neural-networks"},"Neural-networks/Training/Stationary-points":{"id":"Neural-networks/Training/Stationary-points","title":"\u041a\u043b\u0430\u0441\u0441\u044b \u0442\u043e\u0447\u0435\u043a \u0441\u0442\u0430\u0446\u0438\u043e\u043d\u0430\u0440\u043d\u043e\u0441\u0442\u0438","description":"\u0422\u0438\u043f\u044b \u0442\u043e\u0447\u0435\u043a \u0441\u0442\u0430\u0446\u0438\u043e\u043d\u0430\u0440\u043d\u043e\u0441\u0442\u0438 \u0443 \u043d\u0435\u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0444\u0443\u043d\u043a\u0446\u0438\u0438 - \u0442\u043e\u0447\u043a\u0438 \u043c\u0438\u043d\u0438\u043c\u0443\u043c\u0430, \u0442\u043e\u0447\u043a\u0438 \u043c\u0430\u043a\u0441\u0438\u043c\u0443\u043c\u0430 \u0438 \u0442\u043e\u0447\u043a\u0438 \u043f\u0435\u0440\u0435\u0433\u0438\u0431\u0430. \u0418\u0445 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0435 \u0447\u0435\u0440\u0435\u0437 \u0440\u0430\u0437\u043b\u043e\u0436\u0435\u043d\u0438\u0435 \u0422\u0435\u0439\u043b\u043e\u0440\u0430 2-\u0433\u043e \u043f\u043e\u0440\u044f\u0434\u043a\u0430.","sidebar":"Neural-networks"},"Neural-networks/Transformer/Decoder":{"id":"Neural-networks/Transformer/Decoder","title":"\u0414\u0435\u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430","description":"\u0414\u0435\u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a \u0432 \u043c\u043e\u0434\u0435\u043b\u0438 \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430, \u043c\u0435\u0445\u0430\u043d\u0438\u0437\u043c \u0441\u0430\u043c\u043e\u0432\u043d\u0438\u043c\u0430\u043d\u0438\u044f \u0438 \u043a\u0440\u043e\u0441\u0441-\u0432\u043d\u0438\u043c\u0430\u043d\u0438\u044f (self-attention, cross-attention). \u0412\u0438\u0434\u044b \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u044f \u0432 \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430\u0445.","sidebar":"Neural-networks"},"Neural-networks/Transformer/Encoder-self-attention":{"id":"Neural-networks/Transformer/Encoder-self-attention","title":"\u041a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430","description":"\u041a\u043e\u0434\u0438\u0440\u043e\u0432\u0449\u0438\u043a \u0432 \u043c\u043e\u0434\u0435\u043b\u0438 \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430 \u0438 \u043c\u0435\u0445\u0430\u043d\u0438\u0437\u043c \u0441\u0430\u043c\u043e\u0432\u043d\u0438\u043c\u0430\u043d\u0438\u044f (self-attention).","sidebar":"Neural-networks"},"Neural-networks/Transformer/Literature":{"id":"Neural-networks/Transformer/Literature","title":"\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u0430\u044f \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430","description":"","sidebar":"Neural-networks"},"Neural-networks/Transformer/Positional-encoding":{"id":"Neural-networks/Transformer/Positional-encoding","title":"\u041f\u043e\u0437\u0438\u0446\u0438\u043e\u043d\u043d\u043e\u0435 \u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435","description":"\u041f\u043e\u0437\u0438\u0446\u0438\u043e\u043d\u043d\u043e\u0435 \u043a\u043e\u0434\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0432 \u043c\u043e\u0434\u0435\u043b\u0438 \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430 - \u043c\u0435\u0442\u043e\u0434, \u043e\u0431\u043e\u0441\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u0438 \u043f\u0440\u0438\u043c\u0435\u0440 \u0440\u0430\u0431\u043e\u0442\u044b.","sidebar":"Neural-networks"},"Neural-networks/Transformer/Training-transformer":{"id":"Neural-networks/Transformer/Training-transformer","title":"\u041e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430","description":"\u041e\u0441\u043e\u0431\u0435\u043d\u043d\u043e\u0441\u0442\u0438 \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435 \u043c\u043e\u0434\u0435\u043b\u0438 \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430.","sidebar":"Neural-networks"},"Neural-networks/Transformer/Transformer":{"id":"Neural-networks/Transformer/Transformer","title":"\u0422\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440","de
1scription":"\u041c\u043e\u0434\u0435\u043b\u044c \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u0430 - \u0430\u0440\u0445\u0438\u0442\u0435\u043a\u0442\u0443\u0440\u0430, \u043f\u0440\u0435\u0438\u043c\u0443\u0449\u0435\u0441\u0442\u0432\u0430, \u043f\u0440\u0438\u043d\u0446\u0438\u043f \u0440\u0430\u0431\u043e\u0442\u044b.","sidebar":"Neural-networks"}}}}')}}]);
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.