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168        <p>Iterable한 도전 정신, O(1)의 효율적인 프로그래밍, 클린한 코딩을 목표로 하는 딥러닝 엔지니어입니다.</p>
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1383            <ul>
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1440  <div class="archive" style="padding: 0px 35px 0px 35px;">
1441    
1442      <h1 id="page-title" class="page__title"></h1>
1443    
1444    
1445
1446<h3 class="archive__subtitle">최근 포스트</h3>
1447
1448
1449
1450
1451<div class="entries-list">
1452  
1453    
1454
1455
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1457<div class="list__item">
1458  <article class="archive__item" itemscope itemtype="https://schema.org/CreativeWork">
1459    
1460    <h2 class="archive__item-title no_toc" itemprop="headline">
1461      
1462        <a href="/nlp_engineering/NLP_basic_lib2/" rel="permalink">한국어 텍스트 전처리 활용 (filtering)
1463</a>
1464      
1465    </h2>
1466    
1467
1468  <p class="page__meta">
1469    
1470
1471    
1472
1473    
1474      
1475      
1476
1477      <span class="page__meta-readtime">
1478        <i class="far fa-clock" aria-hidden="true"></i>
1479        
1480          4 분 소요
1481        
1482      </span>
1483    
1484  </p>
1485
1486
1487    <p class="archive__item-excerpt" itemprop="description">Introduction
1488
1489  이전 포스팅에서 텍스트 전처리 라이브러리 사용법을 익혔다.
1490  이번 포스팅에서는 라이브러리 기능보다는, nlp 모델 성능을 높이기 위해 필요한 텍스트 전처리(필터링) 방법들에 대해 서술한다.
1491  이전 포스팅과 일부 겹치는 내용이 있을 수 있고, 부실하게...</p>
1492  </article>
1493</div>
1494
1495  
1496    
1497
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1500<div class="list__item">
1501  <article class="archive__item" itemscope itemtype="https://schema.org/CreativeWork">
1502    
1503    <h2 class="archive__item-title no_toc" itemprop="headline">
1504      
1505        <a href="/docker/docker_file/" rel="permalink">Docker(4) - Dockerfile 작성
1506</a>
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1508    </h2>
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1511  <p class="page__meta">
1512    
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1521        <i class="far fa-clock" aria-hidden="true"></i>
1522        
1523          3 분 소요
1524        
1525      </span>
1526    
1527  </p>
1528
1529
1530    <p class="archive__item-excerpt" itemprop="description">Introduction
1531docker Image를 빌드하기 위한 정보를 설정해주는 Dockerfile 작성 방법을 알아본다.
1532
1533</p>
1534  </article>
1535</div>
1536
1537  
1538    
1539
1540
1541
1542<div class="list__item">
1543  <article class="archive__item" itemscope itemtype="https://schema.org/CreativeWork">
1544    
1545    <h2 class="archive__item-title no_toc" itemprop="headline">
1546      
1547        <a href="/python_lib/python_re/" rel="permalink">문자열 매칭을 위한 정규식 라이브러리 (re)
1548</a>
1549      
1550    </h2>
1551    
1552
1553  <p class="page__meta">
1554    
1555
1556    
1557
1558    
1559      
1560      
1561
1562      <span class="page__meta-readtime">
1563        <i class="far fa-clock" aria-hidden="true"></i>
1564        
1565          7 분 소요
1566        
1567      </span>
1568    
1569  </p>
1570
1571
1572    <p class="archive__item-excerpt" itemprop="description">Introduction
1573크롤링을 하거나, NLP 전처리로 인해 문자열의 특정한 패턴을 찾아야 하는 경우가 있다.   
1574파이썬에서는 find라는 문자열 검색 메소드를 기본으로 지원한다.
1575문제는 하나의 문자열의 인덱스만을 반환한다.
1576```python
1577pattern = “node”
1578st...</p>
1579  </article>
1580</div>
1581
1582  
1583    
1584
1585
1586
1587<div class="list__item">
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1589    
1590    <h2 class="archive__item-title no_toc" itemprop="headline">
1591      
1592        <a href="/nlp_engineering/NLP_basic_lib/" rel="permalink">한국어 텍스트 전처리 라이브러리 사용법
1593</a>
1594      
1595    </h2>
1596    
1597
1598  <p class="page__meta">
1599    
1600
1601    
1602
1603    
1604      
1605      
1606
1607      <span class="page__meta-readtime">
1608        <i class="far fa-clock" aria-hidden="true"></i>
1609        
1610          7 분 소요
1611        
1612      </span>
1613    
1614  </p>
1615
1616
1617    <p class="archive__item-excerpt" itemprop="description">Introduction
1618한국어 데이터를 처리하기 위한 파이썬 패키지가 매우 다양하다.
1619이 포스팅에서는 유용하게 사용가능한 한국어 데이터 전처리 파이썬 패키지를 소개한다.
1620
1621  re : 정규화식을 이용한 전처리, -&gt; 기본 사용법은 파이썬 라이브러리 포스팅에서 다뤘음.
1622  Ko...</p>
1623  </article>
1624</div>
1625
1626  
1627    
1628
1629
1630
1631<div class="list__item">
1632  <article class="archive__item" itemscope itemtype="https://schema.org/CreativeWork">
1633    
1634    <h2 class="archive__item-title no_toc" itemprop="headline">
1635      
1636        <a href="/ml_basic/RNN/" rel="permalink">(6) 시퀀스 데이터와 RNN 기초
1637</a>
1638      
1639    </h2>
1640    
1641
1642  <p class="page__meta">
1643    
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1645    
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1647    
1648      
1649      
1650
1651      <span class="page__meta-readtime">
1652        <i class="far fa-clock" aria-hidden="true"></i>
1653        
1654          4 분 소요
1655        
1656      </span>
1657    
1658  </p>
1659
1660
1661    <p class="archive__item-excerpt" itemprop="description">Introduction
1662CNN은 weight sharing과 kernel size에 따른 locality 특성으로, image 데이터를 주로 다루는 CV task에서 좋은 성능을 내고 있다.  
1663반면 부동산 가격이나 음성/문장 데이터와 같은 시퀀스 데이터의 경우에는 auto-reg...</p>
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