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1347    
1348    <li class="md-nav__item md-nav__item--nested">
1349      
1350        
1351        
1352        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_3_7" >
1353        
1354          
1355          <label class="md-nav__link" for="__nav_3_7" id="__nav_3_7_label" tabindex="0">
1356            
1357  
1358  <span class="md-ellipsis">
1359    Compute Optimization
1360  </span>
1361  
1362
1363            <span class="md-nav__icon md-icon"></span>
1364          </label>
1365        
1366        <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_3_7_label" aria-expanded="false">
1367          <label class="md-nav__title" for="__nav_3_7">
1368            <span class="md-nav__icon md-icon"></span>
1369            Compute Optimization
1370          </label>
1371          <ul class="md-nav__list" data-md-scrollfix>
1372            
1373              
1374                
1375  
1376  
1377  
1378  
1379    <li class="md-nav__item">
1380      <a href="../deep_learning/production_pytorch/speed_optimization_basics_numba/" class="md-nav__link">
1381        
1382  
1383  <span class="md-ellipsis">
1384    Speed Optimization Basics Numba
1385  </span>
1386  
1387
1388      </a>
1389    </li>
1390  
1391
1392              
1393            
1394          </ul>
1395        </nav>
1396      
1397    </li>
1398  
1399
1400              
1401            
1402          </ul>
1403        </nav>
1404      
1405    </li>
1406  
1407
1408    
1409      
1410      
1411  
1412  
1413  
1414  
1415    
1416    
1417    
1418      
1419      
1420        
1421      
1422    
1423    
1424    <li class="md-nav__item md-nav__item--nested">
1425      
1426        
1427        
1428        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4" >
1429        
1430          
1431          <label class="md-nav__link" for="__nav_4" id="__nav_4_label" tabindex="0">
1432            
1433  
1434  <span class="md-ellipsis">
1435    Language Model
1436  </span>
1437  
1438
1439            <span class="md-nav__icon md-icon"></span>
1440          </label>
1441        
1442        <nav class="md-nav" data-md-level="1" aria-labelledby="__nav_4_label" aria-expanded="false">
1443          <label class="md-nav__title" for="__nav_4">
1444            <span class="md-nav__icon md-icon"></span>
1445            Language Model
1446          </label>
1447          <ul class="md-nav__list" data-md-scrollfix>
1448            
1449              
1450                
1451  
1452  
1453  
1454  
1455    <li class="md-nav__item">
1456      <a href="../language_model/intro/" class="md-nav__link">
1457        
1458  
1459  <span class="md-ellipsis">
1460    Introduction
1461  </span>
1462  
1463
1464      </a>
1465    </li>
1466  
1467
1468              
1469            
1470              
1471                
1472  
1473  
1474  
1475  
1476    
1477    
1478    
1479      
1480      
1481        
1482      
1483    
1484    
1485    <li class="md-nav__item md-nav__item--nested">
1486      
1487        
1488        
1489        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_2" >
1490        
1491          
1492          <label class="md-nav__link" for="__nav_4_2" id="__nav_4_2_label" tabindex="0">
1493            
1494  
1495  <span class="md-ellipsis">
1496    Containers
1497  </span>
1498  
1499
1500            <span class="md-nav__icon md-icon"></span>
1501          </label>
1502        
1503        <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_2_label" aria-expanded="false">
1504          <label class="md-nav__title" for="__nav_4_2">
1505            <span class="md-nav__icon md-icon"></span>
1506            Containers
1507          </label>
1508          <ul class="md-nav__list" data-md-scrollfix>
1509            
1510              
1511                
1512  
1513  
1514  
1515  
1516    <li class="md-nav__item">
1517      <a href="../language_model/containers/hpc_containers_apptainer/" class="md-nav__link">
1518        
1519  
1520  <span class="md-ellipsis">
1521    HPC Containers with Apptainer
1522  </span>
1523  
1524
1525      </a>
1526    </li>
1527  
1528
1529              
1530            
1531          </ul>
1532        </nav>
1533      
1534    </li>
1535  
1536
1537              
1538            
1539              
1540                
1541  
1542  
1543  
1544  
1545    
1546    
1547    
1548      
1549      
1550        
1551      
1552    
1553    
1554    <li class="md-nav__item md-nav__item--nested">
1555      
1556        
1557        
1558        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_3" >
1559        
1560          
1561          <label class="md-nav__link" for="__nav_4_3" id="__nav_4_3_label" tabindex="0">
1562            
1563  
1564  <span class="md-ellipsis">
1565    LLMs
1566  </span>
1567  
1568
1569            <span class="md-nav__icon md-icon"></span>
1570          </label>
1571        
1572        <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_3_label" aria-expanded="false">
1573          <label class="md-nav__title" for="__nav_4_3">
1574            <span class="md-nav__icon md-icon"></span>
1575            LLMs
1576          </label>
1577          <ul class="md-nav__list" data-md-scrollfix>
1578            
1579              
1580                
1581  
1582  
1583  
1584  
1585    <li class="md-nav__item">
1586      <a href="../language_model/llm/llm_intro_hyperparameter_tuning/" class="md-nav__link">
1587        
1588  
1589  <span class="md-ellipsis">
1590    LLMs Introduction and Hyperparameter Tuning
1591  </span>
1592  
1593
1594      </a>
1595    </li>
1596  
1597
1598              
1599            
1600          </ul>
1601        </nav>
1602      
1603    </li>
1604  
1605
1606              
1607            
1608              
1609                
1610  
1611  
1612  
1613  
1614    
1615    
1616    
1617      
1618      
1619        
1620      
1621    
1622    
1623    <li class="md-nav__item md-nav__item--nested">
1624      
1625        
1626        
1627        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_4" >
1628        
1629          
1630          <label class="md-nav__link" for="__nav_4_4" id="__nav_4_4_label" tabindex="0">
1631            
1632  
1633  <span class="md-ellipsis">
1634    MMLMs
1635  </span>
1636  
1637
1638            <span class="md-nav__icon md-icon"></span>
1639          </label>
1640        
1641        <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_4_label" aria-expanded="false">
1642          <label class="md-nav__title" for="__nav_4_4">
1643            <span class="md-nav__icon md-icon"></span>
1644            MMLMs
1645          </label>
1646          <ul class="md-nav__list" data-md-scrollfix>
1647            
1648              
1649                
1650  
1651  
1652  
1653  
1654    <li class="md-nav__item">
1655      <a href="../language_model/mmlm/mmlm_intro/" class="md-nav__link">
1656        
1657  
1658  <span class="md-ellipsis">
1659    MMLMs Introduction
1660  </span>
1661  
1662
1663      </a>
1664    </li>
1665  
1666
1667              
1668            
1669          </ul>
1670        </nav>
1671      
1672    </li>
1673  
1674
1675              
1676            
1677              
1678                
1679  
1680  
1681  
1682  
1683    
1684    
1685    
1686      
1687      
1688        
1689      
1690    
1691    
1692    <li class="md-nav__item md-nav__item--nested">
1693      
1694        
1695        
1696        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_5" >
1697        
1698          
1699          <label class="md-nav__link" for="__nav_4_5" id="__nav_4_5_label" tabindex="0">
1700            
1701  
1702  <span class="md-ellipsis">
1703    RAG
1704  </span>
1705  
1706
1707            <span class="md-nav__icon md-icon"></span>
1708          </label>
1709        
1710        <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_5_label" aria-expanded="false">
1711          <label class="md-nav__title" for="__nav_4_5">
1712            <span class="md-nav__icon md-icon"></span>
1713            RAG
1714          </label>
1715          <ul class="md-nav__list" data-md-scrollfix>
1716            
1717              
1718                
1719  
1720  
1721  
1722  
1723    <li class="md-nav__item">
1724      <a href="../language_model/rag/embedding/" class="md-nav__link">
1725        
1726  
1727  <span class="md-ellipsis">
1728    Embeddings Introduction
1729  </span>
1730  
1731
1732      </a>
1733    </li>
1734  
1735
1736              
1737            
1738          </ul>
1739        </nav>
1740      
1741    </li>
1742  
1743
1744              
1745            
1746          </ul>
1747        </nav>
1748      
1749    </li>
1750  
1751
1752    
1753      
1754      
1755  
1756  
1757  
1758  
1759    
1760    
1761    
1762      
1763      
1764        
1765      
1766    
1767    
1768    <li class="md-nav__item md-nav__item--nested">
1769      
1770        
1771        
1772        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_5" >
1773        
1774          
1775          <label class="md-nav__link" for="__nav_5" id="__nav_5_label" tabindex="0">
1776            
1777  
1778  <span class="md-ellipsis">
1779    Machine Learning
1780  </span>
1781  
1782
1783            <span class="md-nav__icon md-icon"></span>
1784          </label>
1785        
1786        <nav class="md-nav" data-md-level="1" aria-labelledby="__nav_5_label" aria-expanded="false">
1787          <label class="md-nav__title" for="__nav_5">
1788            <span class="md-nav__icon md-icon"></span>
1789            Machine Learning
1790          </label>
1791          <ul class="md-nav__list" data-md-scrollfix>
1792            
1793              
1794                
1795  
1796  
1797  
1798  
1799    <li class="md-nav__item">
1800      <a href="../machine_learning/intro/" class="md-nav__link">
1801        
1802  
1803  <span class="md-ellipsis">
1804    Introduction
1805  </span>
1806  
1807
1808      </a>
1809    </li>
1810  
1811
1812              
1813            
1814              
1815                
1816  
1817  
1818  
1819  
1820    
1821    
1822    
1823      
1824      
1825        
1826      
1827    
1828    
1829    <li class="md-nav__item md-nav__item--nested">
1830      
1831        
1832        
1833        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_5_2" >
1834        
1835          
1836          <label class="md-nav__link" for="__nav_5_2" id="__nav_5_2_label" tabindex="0">
1837            
1838  
1839  <span class="md-ellipsis">
1840    RAPIDS cuDF
1841  </span>
1842  
1843
1844            <span class="md-nav__icon md-icon"></span>
1845          </label>
1846        
1847        <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_5_2_label" aria-expanded="false">
1848          <label class="md-nav__title" for="__nav_5_2">
1849            <span class="md-nav__icon md-icon"></span>
1850            RAPIDS cuDF
1851          </label>
1852          <ul class="md-nav__list" data-md-scrollfix>
1853            
1854              
1855                
1856  
1857  
1858  
1859  
1860    <li class="md-nav__item">
1861      <a href="../machine_learning/gpu/rapids_cudf/" class="md-nav__link">
1862        
1863  
1864  <span class="md-ellipsis">
1865    GPU DataFrames
1866  </span>
1867  
1868
1869      </a>
1870    </li>
1871  
1872
1873              
1874            
1875              
1876                
1877  
1878  
1879  
1880  
1881    <li class="md-nav__item">
1882      <a href="../machine_learning/gpu/gpu_fractional_differencing/" class="md-nav__link">
1883        
1884  
1885  <span class="md-ellipsis">
1886    GPU/CPU Fractional Differencing
1887  </span>
1888  
1889
1890      </a>
1891    </li>
1892  
1893
1894              
1895            
1896          </ul>
1897        </nav>
1898      
1899    </li>
1900  
1901
1902              
1903            
1904          </ul>
1905        </nav>
1906      
1907    </li>
1908  
1909
1910    
1911      
1912      
1913  
1914  
1915  
1916  
1917    
1918    
1919    
1920      
1921      
1922        
1923      
1924    
1925    
1926    <li class="md-nav__item md-nav__item--nested">
1927      
1928        
1929        
1930        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_6" >
1931        
1932          
1933          <label class="md-nav__link" for="__nav_6" id="__nav_6_label" tabindex="0">
1934            
1935  
1936  <span class="md-ellipsis">
1937    Programming
1938  </span>
1939  
1940
1941            <span class="md-nav__icon md-icon"></span>
1942          </label>
1943        
1944        <nav class="md-nav" data-md-level="1" aria-labelledby="__nav_6_label" aria-expanded="false">
1945          <label class="md-nav__title" for="__nav_6">
1946            <span class="md-nav__icon md-icon"></span>
1947            Programming
1948          </label>
1949          <ul class="md-nav__list" data-md-scrollfix>
1950            
1951              
1952                
1953  
1954  
1955  
1956  
1957    <li class="md-nav__item">
1958      <a href="../programming/intro/" class="md-nav__link">
1959        
1960  
1961  <span class="md-ellipsis">
1962    Introduction
1963  </span>
1964  
1965
1966      </a>
1967    </li>
1968  
1969
1970              
1971            
1972              
1973                
1974  
1975  
1976  
1977  
1978    <li class="md-nav__item">
1979      <a href="../programming/cpp/cpp/" class="md-nav__link">
1980        
1981  
1982  <span class="md-ellipsis">
1983    C++
1984  </span>
1985  
1986
1987      </a>
1988    </li>
1989  
1990
1991              
1992            
1993              
1994                
1995  
1996  
1997  
1998  
1999    <li class="md-nav__item">
2000      <a href="../programming/bash/bash/" class="md-nav__link">
2001        
2002  
2003  <span class="md-ellipsis">
2004    Bash
2005  </span>
2006  
2007
2008      </a>
2009    </li>
2010  
2011
2012              
2013            
2014              
2015                
2016  
2017  
2018  
2019  
2020    <li class="md-nav__item">
2021      <a href="../programming/python/python/" class="md-nav__link">
2022        
2023  
2024  <span class="md-ellipsis">
2025    Python
2026  </span>
2027  
2028
2029      </a>
2030    </li>
2031  
2032
2033              
2034            
2035              
2036                
2037  
2038  
2039  
2040  
2041    <li class="md-nav__item">
2042      <a href="../programming/r/r/" class="md-nav__link">
2043        
2044  
2045  <span class="md-ellipsis">
2046    R
2047  </span>
2048  
2049
2050      </a>
2051    </li>
2052  
2053
2054              
2055            
2056              
2057                
2058  
2059  
2060  
2061  
2062    <li class="md-nav__item">
2063      <a href="../programming/javascript/javascript/" class="md-nav__link">
2064        
2065  
2066  <span class="md-ellipsis">
2067    Javascript
2068  </span>
2069  
2070
2071      </a>
2072    </li>
2073  
2074
2075              
2076            
2077              
2078                
2079  
2080  
2081  
2082  
2083    <li class="md-nav__item">
2084      <a href="../programming/electron/electron/" class="md-nav__link">
2085        
2086  
2087  <span class="md-ellipsis">
2088    Electron
2089  </span>
2090  
2091
2092      </a>
2093    </li>
2094  
2095
2096              
2097            
2098              
2099                
2100  
2101  
2102  
2103  
2104    <li class="md-nav__item">
2105      <a href="../programming/sympy/calculus_sympy/" class="md-nav__link">
2106        
2107  
2108  <span class="md-ellipsis">
2109    Sympy
2110  </span>
2111  
2112
2113      </a>
2114    </li>
2115  
2116
2117              
2118            
2119              
2120                
2121  
2122  
2123  
2124  
2125    <li class="md-nav__item">
2126      <a href="../programming/numpycupy/linalg_numpy_cupy/" class="md-nav__link">
2127        
2128  
2129  <span class="md-ellipsis">
2130    NumPy and CuPy
2131  </span>
2132  
2133
2134      </a>
2135    </li>
2136  
2137
2138              
2139            
2140          </ul>
2141        </nav>
2142      
2143    </li>
2144  
2145
2146    
2147      
2148      
2149  
2150  
2151  
2152  
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2154    
2155    
2156      
2157      
2158        
2159      
2160    
2161    
2162    <li class="md-nav__item md-nav__item--nested">
2163      
2164        
2165        
2166        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7" >
2167        
2168          
2169          <label class="md-nav__link" for="__nav_7" id="__nav_7_label" tabindex="0">
2170            
2171  
2172  <span class="md-ellipsis">
2173    Data Engineering
2174  </span>
2175  
2176
2177            <span class="md-nav__icon md-icon"></span>
2178          </label>
2179        
2180        <nav class="md-nav" data-md-level="1" aria-labelledby="__nav_7_label" aria-expanded="false">
2181          <label class="md-nav__title" for="__nav_7">
2182            <span class="md-nav__icon md-icon"></span>
2183            Data Engineering
2184          </label>
2185          <ul class="md-nav__list" data-md-scrollfix>
2186            
2187              
2188                
2189  
2190  
2191  
2192  
2193    
2194    
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2196      
2197      
2198        
2199      
2200    
2201    
2202    <li class="md-nav__item md-nav__item--nested">
2203      
2204        
2205        
2206        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_1" >
2207        
2208          
2209          <label class="md-nav__link" for="__nav_7_1" id="__nav_7_1_label" tabindex="0">
2210            
2211  
2212  <span class="md-ellipsis">
2213    Cassandra (NoSQL)
2214  </span>
2215  
2216
2217            <span class="md-nav__icon md-icon"></span>
2218          </label>
2219        
2220        <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_1_label" aria-expanded="false">
2221          <label class="md-nav__title" for="__nav_7_1">
2222            <span class="md-nav__icon md-icon"></span>
2223            Cassandra (NoSQL)
2224          </label>
2225          <ul class="md-nav__list" data-md-scrollfix>
2226            
2227              
2228                
2229  
2230  
2231  
2232  
2233    <li class="md-nav__item">
2234      <a href="../data_engineering/nosql/cassandra/intro/" class="md-nav__link">
2235        
2236  
2237  <span class="md-ellipsis">
2238    Introduction
2239  </span>
2240  
2241
2242      </a>
2243    </li>
2244  
2245
2246              
2247            
2248              
2249                
2250  
2251  
2252  
2253  
2254    <li class="md-nav__item">
2255      <a href="../data_engineering/nosql/cassandra/setting_up_cluster/" class="md-nav__link">
2256        
2257  
2258  <span class="md-ellipsis">
2259    Cassandra Cluster Setup
2260  </span>
2261  
2262
2263      </a>
2264    </li>
2265  
2266
2267              
2268            
2269          </ul>
2270        </nav>
2271      
2272    </li>
2273  
2274
2275              
2276            
2277          </ul>
2278        </nav>
2279      
2280    </li>
2281  
2282
2283    
2284      
2285      
2286  
2287  
2288  
2289  
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2291    
2292    
2293      
2294      
2295        
2296      
2297    
2298    
2299    <li class="md-nav__item md-nav__item--nested">
2300      
2301        
2302        
2303        <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_8" >
2304        
2305          
2306          <label class="md-nav__link" for="__nav_8" id="__nav_8_label" tabindex="0">
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2704<h1 id="about-us">About Us<a class="headerlink" href="#about-us" title="Permanent link">&para;</a></h1>
2705<p>We deploy a top-down approach that enables you to grasp deep learning and deep reinforcement learning theories and code easily and quickly. We have open-sourced all our materials through our <a href="https://www.deeplearningwizard.com/deep_learning/course_progression/">Deep Learning Wizard Tutorials</a>. For visual learners, feel free to sign up for our <a href="https://www.udemy.com/practical-deep-learning-with-pytorch/?couponCode=DEEPWIZARD">video course</a> and join over 6000 deep learning wizards.</p>
2706<p>To this date, we have taught thousands of students across more than 120+ countries from students in high school to postgraduates and professionals in leading MNCs and research institutions around the world.</p>
2707<h2 id="core-contributor">Core Contributor<a class="headerlink" href="#core-contributor" title="Permanent link">&para;</a></h2>
2708<div class="admonition abstract">
2709<p class="admonition-title">Ritchie Ng</p>
2710<p><strong>Industry</strong>: As the Group Head of Data &amp; AI at Eastspring Investments, I spearhead engineering, governance, and strategy across data and machine learning in 13 countries with Assets Under Management (AUM) exceeding USD 220 billion.</p>
2711<p><strong>Academia</strong>: Serving in the capacity of a Visiting Research Scholar at NExT++ Lab, jointly setup between NUS and Tsinghua University, I focus on applied deep learning research for Asian systematic trading strategies and the development of financial Large Language Models (LLM) using multimodal and multilingual data.</p>
2712<p><strong>Education</strong>: Master's degree from Imperial College London and Bachelor's degree from NUS.</p>
2713<p><strong>About</strong>: ritchieng.live</p>
2714<p><strong>Notes</strong>: ritchieng.com</p>
2715<p><strong>Guides</strong>: deeplearningwizard.com</p>
2716</div>
2717<h2 id="individual-supporters">Individual Supporters<a class="headerlink" href="#individual-supporters" title="Permanent link">&para;</a></h2>
2718<div class="admonition abstract">
2719<p class="admonition-title">Alfredo Canziani</p>
2720<p>Alfredo is the main person who inspired Ritchie to open-source Deep Learning Wizard's materials. We are very grateful for his advice particular in the space of open-source projects, deep learning and PyTorch.</p>
2721<p>He is currently working as an Assistant Professor at Courant Institute of Mathematical Sciences, under the guidance of professor Yann LeCun.</p>
2722<p>Do check out his latest <a href="https://github.com/Atcold/pytorch-Deep-Learning-Minicourse">mini-course on PyTorch</a> that was held in Princeton University and was delivered with Ritchie Ng at AMMI (AIMS) Kigali, Rwanda supported by Google and Facebook.</p>
2723</div>
2724<div class="admonition abstract">
2725<p class="admonition-title">Marek Bardonski</p>
2726<p>Since graduation, Marek has been working on state-of-the-art research. He was involved in inventing the system that diagnoses problems with Ubuntu packages using Machine Learning and in improving the detection accuracy of breast cancer using Deep Learning, each time leading 40 highly skilled Machine Learning/Deep Learning engineers for over 
27266 months.</p>
2727<p>NASA noticed his unique skills and asked him to manage a project aiming to improve the International Space Station rotation algorithm that would allow them to collect enough power from solar panels while preventing them from overheating. The project was successful and generated a huge ROI for NASA. Marek has been honored by multiple Harvard professors and the Director of Advanced Exploration Systems at NASA, who signed an official Letter of Recommendation.</p>
2728<p>Since his first summer of university coursework, Marek has participated in four internships at NVIDIA HQ and Microsoft HQ. He also spent one year in NVIDIA Switzerland optimizing Deep Learning inference for self-driving cars and, by implementing very efficient Deep Learning algorithms in the GPU assembly language, improving the speed of Tesla’s cars self-driving engine inference. He's currently the Head of AI at <a href="https://sigmoidal.io/">Sigmoidal</a>.</p>
2729</div>
2730<div class="admonition abstract">
2731<p class="admonition-title">Jie Fu</p>
2732<p>Jie Fu is a happy and funny machine learning researcher (principal investigator), at Hong Kong University of Science and Technology (HKUST), with his human-friendly big AI dream.</p>
2733<p>He worked as a postdoc with Yoshua Bengio at University of Montreal, Quebec AI Institute (Mila), funded by Microsoft Research Montreal. He was an IVADO postdoc fellow working with Chris Pal at Polytechnique Montreal, Quebec AI Institute (Mila). He obtained his PhD from National University of Singapore under the supervision of Tat-Seng Chua. He received ICLR 2021 Outstanding Paper Award.</p>
2734<p>He is currently working towards system-2 deep learning and its adaption to various real-world tasks, including AI for Science (drug discovery in particular) and AI for Social Good that can benefit all of society. He is also broadly interested in general deep learning, reinforcement learning, and language processing.</p>
2735<p>Check out his profile link at <a href="http://bigaidream.github.io/">bigaidream.github.io</a></p>
2736</div>
2737<h2 id="corporate-supporters">Corporate Supporters<a class="headerlink" href="#corporate-supporters" title="Permanent link">&para;</a></h2>
2738<div class="admonition tip">
2739<p class="admonition-title">"NVIDIA Inception Partner</p>
2740<p><center><img src="https://res.cloudinary.com/ritchieng/image/upload/v1532596192/deeplearningwizard.com/nvidia_inception.png" style="width:200px"/></center></p>
2741<p>Deep Learning Wizard is proudly an NVIDIA Inception Partner, empowering people across the world to leverage on deep learning via open-source programming languages and frameworks to solve problems.</p>
2742</div>
2743<div class="admonition warning">
2744<p class="admonition-title">Amazon AWS Activate Programme Startup</p>
2745<p><center><img src="https://res.cloudinary.com/ritchieng/image/upload/v1563421301/logos/aws_activate.png" style="width:200px"/></center></p>
2746<p>Deep Learning Wizard is also supported by the Amazon AWS Activate Programme, Portfolio Plus, allowing us to have the infrastructure to scale and grow.   </p>
2747</div>
2748<h2 id="citation">Citation<a class="headerlink" href="#citation" title="Permanent link">&para;</a></h2>
2749<p>If you have found these useful in your research, presentations, school work, projects or workshops, feel free to cite using this DOI.</p>
2750<p><a href="https://zenodo.org/badge/latestdoi/139945544"><img alt="DOI" src="https://zenodo.org/badge/139945544.svg" /></a></p>
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