{"id":3614,"date":"2019-07-27T20:55:46","date_gmt":"2019-07-27T12:55:46","guid":{"rendered":"https:\/\/tao0.date\/?p=3614"},"modified":"2019-07-27T20:55:57","modified_gmt":"2019-07-27T12:55:57","slug":"githubzuizhumingde20gepythonjiqixuexixiangmu","status":"publish","type":"post","link":"https:\/\/tao0.date\/?p=3614","title":{"rendered":"GitHub\u6700\u8457\u540d\u768420\u4e2aPython\u673a\u5668\u5b66\u4e60\u9879\u76ee"},"content":{"rendered":"<p><strong>\u5f00\u6e90\u662f\u6280\u672f\u521b\u65b0\u548c\u5feb\u901f\u53d1\u5c55\u7684\u6838\u5fc3\u3002\u8fd9\u7bc7\u6587\u7ae0\u5411\u4f60\u5c55\u793aPython\u673a\u5668\u5b66\u4e60\u5f00\u6e90\u9879\u76ee\u4ee5\u53ca\u5728\u5206\u6790\u8fc7\u7a0b\u4e2d\u53d1\u73b0\u7684\u975e\u5e38\u6709\u8da3\u7684\u89c1\u89e3\u548c\u8d8b\u52bf\u3002<\/strong><\/p>\n<p><img decoding=\"async\" src=\"https:\/\/tao0.date\/wp-content\/uploads\/2019\/07\/20190727205546-b3b39.octet-stream\" alt=\"640?wxfrom=5&amp;wx_lazy=1\" \/><\/p>\n<p>\u6211\u4eec\u5206\u6790\u4e86GitHub\u4e0a\u7684\u524d20\u540dPython\u673a\u5668\u5b66\u4e60\u9879\u76ee\uff0c\u53d1\u73b0scikit-Learn\uff0cPyLearn2\u548cNuPic\u662f\u8d21\u732e\u6700\u79ef\u6781\u7684\u9879\u76ee\u3002\u8ba9\u6211\u4eec\u4e00\u8d77\u5728Github\u4e0a\u63a2\u7d22\u8fd9\u4e9b\u6d41\u884c\u7684\u9879\u76ee\uff01<\/p>\n<p><strong>1<\/strong><\/p>\n<p>Scikit-learn\uff1aScikit-learn \u662f\u57fa\u4e8eScipy\u4e3a\u673a\u5668\u5b66\u4e60\u5efa\u9020\u7684\u7684\u4e00\u4e2aPython\u6a21\u5757\uff0c\u4ed6\u7684\u7279\u8272\u5c31\u662f\u591a\u6837\u5316\u7684\u5206\u7c7b\uff0c\u56de\u5f52\u548c\u805a\u7c7b\u7684\u7b97\u6cd5\u5305\u62ec\u652f\u6301\u5411\u91cf\u673a\uff0c\u903b\u8f91\u56de\u5f52\uff0c\u6734\u7d20\u8d1d\u53f6\u65af\u5206\u7c7b\u5668\uff0c\u968f\u673a\u68ee\u6797\uff0cGradient Boosting\uff0c\u805a\u7c7b\u7b97\u6cd5\u548cDBSCAN\u3002\u800c\u4e14\u4e5f\u8bbe\u8ba1\u51fa\u4e86Python numerical\u548cscientific libraries Numpy and Scipy<\/p>\n<p>https:\/\/github.com\/scikit-learn\/scikit-learn<\/p>\n<p><strong>2<\/strong><\/p>\n<p>Pylearn2\uff1aPylearn\u662f\u4e00\u4e2a\u8ba9\u673a\u5668\u5b66\u4e60\u7814\u7a76\u7b80\u5355\u5316\u7684\u57fa\u4e8eTheano\u7684\u5e93\u7a0b\u5e8f\u3002<\/p>\n<p>https:\/\/github.com\/lisa-lab\/pylearn2<\/p>\n<p><strong>3<\/strong><\/p>\n<p>NuPIC\uff1aNuPIC\u662f\u4e00\u4e2a\u4ee5HTM\u5b66\u4e60\u7b97\u6cd5\u4e3a\u5de5\u5177\u7684\u673a\u5668\u667a\u80fd\u5e73\u53f0\u3002HTM\u662f\u76ae\u5c42\u7684\u7cbe\u786e\u8ba1\u7b97\u65b9\u6cd5\u3002HTM\u7684\u6838\u5fc3\u662f\u57fa\u4e8e\u65f6\u95f4\u7684\u6301\u7eed\u5b66\u4e60\u7b97\u6cd5\u548c\u50a8\u5b58\u548c\u64a4\u9500\u7684\u65f6\u7a7a\u6a21\u5f0f\u3002NuPIC\u9002\u5408\u4e8e\u5404\u79cd\u5404\u6837\u7684\u95ee\u9898,\u5c24\u5176\u662f\u68c0\u6d4b\u5f02\u5e38\u548c\u9884\u6d4b\u7684\u6d41\u6570\u636e\u6765\u6e90\u3002<\/p>\n<p>https:\/\/github.com\/numenta\/nupic<\/p>\n<p><strong>4<\/strong><\/p>\n<p>Nilearn\uff1aNilearn \u662f\u4e00\u4e2a\u80fd\u591f\u5feb\u901f\u7edf\u8ba1\u5b66\u4e60\u795e\u7ecf\u5f71\u50cf\u6570\u636e\u7684Python\u6a21\u5757\u3002\u5b83\u5229\u7528Python\u8bed\u8a00\u4e2d\u7684scikit-learn \u5de5\u5177\u7bb1\u548c\u4e00\u4e9b\u8fdb\u884c\u9884\u6d4b\u5efa\u6a21\uff0c\u5206\u7c7b\uff0c\u89e3\u7801\uff0c\u8fde\u901a\u6027\u5206\u6790\u7684\u5e94\u7528\u7a0b\u5e8f\u6765\u8fdb\u884c\u591a\u5143\u7684\u7edf\u8ba1\u3002<\/p>\n<p>https:\/\/github.com\/nilearn\/nilearn<\/p>\n<p><strong>5<\/strong><\/p>\n<p>PyBrain\uff1aPybrain\u662f\u57fa\u4e8ePython\u8bed\u8a00\u5f3a\u5316\u5b66\u4e60\uff0c\u4eba\u5de5\u667a\u80fd\uff0c\u795e\u7ecf\u7f51\u7edc\u5e93\u7684\u7b80\u79f0\u3002 \u5b83\u7684\u76ee\u6807\u662f\u63d0\u4f9b\u7075\u6d3b\u3001\u5bb9\u6613\u4f7f\u7528\u5e76\u4e14\u5f3a\u5927\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u548c\u8fdb\u884c\u5404\u79cd\u5404\u6837\u7684\u9884\u5b9a\u4e49\u7684\u73af\u5883\u4e2d\u6d4b\u8bd5\u6765\u6bd4\u8f83\u4f60\u7684\u7b97\u6cd5\u3002<\/p>\n<p>https:\/\/github.com\/pybrain\/pybrain<\/p>\n<p><strong>6<\/strong><\/p>\n<p>Pattern\uff1aPattern \u662fPython\u8bed\u8a00\u4e0b\u7684\u4e00\u4e2a\u7f51\u7edc\u6316\u6398\u6a21\u5757\u3002\u5b83\u4e3a\u6570\u636e\u6316\u6398\uff0c\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff0c\u7f51\u7edc\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60\u63d0\u4f9b\u5de5\u5177\u3002\u5b83\u652f\u6301\u5411\u91cf\u7a7a\u95f4\u6a21\u578b\u3001\u805a\u7c7b\u3001\u652f\u6301\u5411\u91cf\u673a\u548c\u611f\u77e5\u673a\u5e76\u4e14\u7528KNN\u5206\u7c7b\u6cd5\u8fdb\u884c\u5206\u7c7b\u3002<\/p>\n<p>https:\/\/github.com\/clips\/pattern<\/p>\n<p><strong>7<\/strong><\/p>\n<p>Fuel\uff1aFuel\u4e3a\u4f60\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u63d0\u4f9b\u6570\u636e\u3002\u4ed6\u6709\u4e00\u4e2a\u5171\u4eab\u5982MNIST, CIFAR-10 (\u56fe\u7247\u6570\u636e\u96c6), Google&#8217;s One Billion Words (\u6587\u5b57)\u8fd9\u7c7b\u6570\u636e\u96c6\u7684\u63a5\u53e3\u3002\u4f60\u4f7f\u7528\u4ed6\u6765\u901a\u8fc7\u5f88\u591a\u79cd\u7684\u65b9\u5f0f\u6765\u66ff\u4ee3\u81ea\u5df1\u7684\u6570\u636e\u3002<\/p>\n<p>http:\/\/www.github.com\/mila-udem\/fuel<\/p>\n<p><strong>8<\/strong><\/p>\n<p>Bob\uff1aBob\u662f\u4e00\u4e2a\u514d\u8d39\u7684\u4fe1\u53f7\u5904\u7406\u548c\u673a\u5668\u5b66\u4e60\u7684\u5de5\u5177\u3002\u5b83\u7684\u5de5\u5177\u7bb1\u662f\u7528Python\u548cC++\u8bed\u8a00\u5171\u540c\u7f16\u5199\u7684\uff0c\u5b83\u7684\u8bbe\u8ba1\u76ee\u7684\u662f\u53d8\u5f97\u66f4\u52a0\u9ad8\u6548\u5e76\u4e14\u51cf\u5c11\u5f00\u53d1\u65f6\u95f4\uff0c\u5b83\u662f\u7531\u5904\u7406\u56fe\u50cf\u5de5\u5177,\u97f3\u9891\u548c\u89c6\u9891\u5904\u7406\u3001\u673a\u5668\u5b66\u4e60\u548c\u6a21\u5f0f\u8bc6\u522b\u7684\u5927\u91cf\u8f6f\u4ef6\u5305\u6784\u6210\u7684\u3002<\/p>\n<p>www.github.com\/idiap\/bob<\/p>\n<p><strong>9<\/strong><\/p>\n<p>Skdata\uff1aSkdata\u662f\u673a\u5668\u5b66\u4e60\u548c\u7edf\u8ba1\u7684\u6570\u636e\u96c6\u7684\u5e93\u7a0b\u5e8f\u3002\u8fd9\u4e2a\u6a21\u5757\u5bf9\u4e8e\u73a9\u5177\u95ee\u9898\uff0c\u6d41\u884c\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u81ea\u7136\u8bed\u8a00\u7684\u6570\u636e\u96c6\u63d0\u4f9b\u6807\u51c6\u7684Python\u8bed\u8a00\u7684\u4f7f\u7528\u3002<\/p>\n<p>www.github.com\/jaberg\/skdata<\/p>\n<p><strong>10<\/strong><\/p>\n<p>MILK\uff1aMILK\u662fPython\u8bed\u8a00\u4e0b\u7684\u673a\u5668\u5b66\u4e60\u5de5\u5177\u5305\u3002\u5b83\u4e3b\u8981\u662f\u5728\u5f88\u591a\u53ef\u5f97\u5230\u7684\u5206\u7c7b\u6bd4\u5982SVMS,K-NN,\u968f\u673a\u68ee\u6797\uff0c\u51b3\u7b56\u6811\u4e2d\u4f7f\u7528\u76d1\u7763\u5206\u7c7b\u6cd5\u3002 \u5b83\u8fd8\u6267\u884c\u7279\u5f81\u9009\u62e9\u3002 \u8fd9\u4e9b\u5206\u7c7b\u5668\u5728\u8bb8\u591a\u65b9\u9762\u76f8\u7ed3\u5408,\u53ef\u4ee5\u5f62\u6210\u4e0d\u540c\u7684\u4f8b\u5982\u65e0\u76d1\u7763\u5b66\u4e60\u3001\u5bc6\u5207\u5173\u7cfb\u91d1\u4f20\u64ad\u548c\u7531MILK\u652f\u6301\u7684K-means\u805a\u7c7b\u7b49\u5206\u7c7b\u7cfb\u7edf\u3002<\/p>\n<p>www.github.com\/luispedro\/milk<\/p>\n<p><strong>11<\/strong><\/p>\n<p>IEPY\uff1aIEPY\u662f\u4e00\u4e2a\u4e13\u6ce8\u4e8e\u5173\u7cfb\u62bd\u53d6\u7684\u5f00\u6e90\u6027\u4fe1\u606f\u62bd\u53d6\u5de5\u5177\u3002\u5b83\u4e3b\u8981\u9488\u5bf9\u7684\u662f\u9700\u8981\u5bf9\u5927\u578b\u6570\u636e\u96c6\u8fdb\u884c\u4fe1\u606f\u63d0\u53d6\u7684\u7528\u6237\u548c\u60f3\u8981\u5c1d\u8bd5\u65b0\u7684\u7b97\u6cd5\u7684\u79d1\u5b66\u5bb6\u3002<\/p>\n<p>www.github.com\/machinalis\/iepy<\/p>\n<p><strong>12<\/strong><\/p>\n<p>Quepy\uff1aQuepy\u662f\u901a\u8fc7\u6539\u53d8\u81ea\u7136\u8bed\u8a00\u95ee\u9898\u4ece\u800c\u5728\u6570\u636e\u5e93\u67e5\u8be2\u8bed\u8a00\u4e2d\u8fdb\u884c\u67e5\u8be2\u7684\u4e00\u4e2aPython\u6846\u67b6\u3002\u4ed6\u53ef\u4ee5\u7b80\u5355\u7684\u88ab\u5b9a\u4e49\u4e3a\u5728\u81ea\u7136\u8bed\u8a00\u548c\u6570\u636e\u5e93\u67e5\u8be2\u4e2d\u4e0d\u540c\u7c7b\u578b\u7684\u95ee\u9898\u3002\u6240\u4ee5\uff0c\u4f60\u4e0d\u7528\u7f16\u7801\u5c31\u53ef\u4ee5\u5efa\u7acb\u4f60\u81ea\u5df1\u7684\u4e00\u4e2a\u7528\u81ea\u7136\u8bed\u8a00\u8fdb\u5165\u4f60\u7684\u6570\u636e\u5e93\u7684\u7cfb\u7edf\u3002\u73b0\u5728Quepy\u63d0\u4f9b\u5bf9\u4e8eSparql\u548cMQL\u67e5\u8be2\u8bed\u8a00\u7684\u652f\u6301\u3002\u5e76\u4e14\u8ba1\u5212\u5c06\u5b83\u5ef6\u4f38\u5230\u5176\u4ed6\u7684\u6570\u636e\u5e93\u67e5\u8be2\u8bed\u8a00\u3002<\/p>\n<p>www.github.com\/machinalis\/quepy<\/p>\n<p><strong>13<\/strong><\/p>\n<p>Hebel\uff1aHebel\u662f\u5728Python\u8bed\u8a00\u4e2d\u5bf9\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u6df1\u5ea6\u5b66\u4e60\u7684\u4e00\u4e2a\u5e93\u7a0b\u5e8f\uff0c\u5b83\u4f7f\u7528\u7684\u662f\u901a\u8fc7PyCUDA\u6765\u8fdb\u884cGPU\u548cCUDA\u7684\u52a0\u901f\u3002\u5b83\u662f\u6700\u91cd\u8981\u7684\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u7684\u7c7b\u578b\u7684\u5de5\u5177\u800c\u4e14\u80fd\u63d0\u4f9b\u4e00\u4e9b\u4e0d\u540c\u7684\u6d3b\u52a8\u51fd\u6570\u7684\u6fc0\u6d3b\u529f\u80fd\uff0c\u4f8b\u5982\u52a8\u529b\uff0c\u6d85\u65af\u6377\u7f57\u592b\u52a8\u529b\uff0c\u4fe1\u53f7\u4e22\u5931\u548c\u505c\u6b62\u6cd5\u3002<\/p>\n<p>www.github.com\/hannes-brt\/hebel<\/p>\n<p><strong>14<\/strong><\/p>\n<p>mlxtend\uff1a\u5b83\u662f\u4e00\u4e2a\u7531\u6709\u7528\u7684\u5de5\u5177\u548c\u65e5\u5e38\u6570\u636e\u79d1\u5b66\u4efb\u52a1\u7684\u6269\u5c55\u7ec4\u6210\u7684\u4e00\u4e2a\u5e93\u7a0b\u5e8f\u3002<\/p>\n<p>www.github.com\/rasbt\/mlxtend<\/p>\n<p><strong>15<\/strong><\/p>\n<p>nolearn\uff1a\u8fd9\u4e2a\u7a0b\u5e8f\u5305\u5bb9\u7eb3\u4e86\u5927\u91cf\u80fd\u5bf9\u4f60\u5b8c\u6210\u673a\u5668\u5b66\u4e60\u4efb\u52a1\u6709\u5e2e\u52a9\u7684\u5b9e\u7528\u7a0b\u5e8f\u6a21\u5757\u3002\u5176\u4e2d\u5927\u91cf\u7684\u6a21\u5757\u548cscikit-learn\u4e00\u8d77\u5de5\u4f5c\uff0c\u5176\u5b83\u7684\u901a\u5e38\u66f4\u6709\u7528\u3002<\/p>\n<p>www.github.com\/dnouri\/nolearn<\/p>\n<p><strong>16<\/strong><\/p>\n<p>Ramp\uff1aRamp\u662f\u4e00\u4e2a\u5728Python\u8bed\u8a00\u4e0b\u5236\u5b9a\u673a\u5668\u5b66\u4e60\u4e2d\u52a0\u5feb\u539f\u578b\u8bbe\u8ba1\u7684\u89e3\u51b3\u65b9\u6848\u7684\u5e93\u7a0b\u5e8f\u3002\u4ed6\u662f\u4e00\u4e2a\u8f7b\u578b\u7684pandas-based\u673a\u5668\u5b66\u4e60\u4e2d\u53ef\u63d2\u5165\u7684\u6846\u67b6\uff0c\u5b83\u73b0\u5b58\u7684Python\u8bed\u8a00\u4e0b\u7684\u673a\u5668\u5b66\u4e60\u548c\u7edf\u8ba1\u5de5\u5177\uff08\u6bd4\u5982scikit-learn,rpy2\u7b49\uff09Ramp\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u58f0\u660e\u6027\u8bed\u6cd5\u63a2\u7d22\u529f\u80fd\u4ece\u800c\u80fd\u591f\u5feb\u901f\u6709\u6548\u5730\u5b9e\u65bd\u7b97\u6cd5\u548c\u8f6c\u6362\u3002<\/p>\n<p>www.github.com\/kvh\/ramp<\/p>\n<p><strong>17<\/strong><\/p>\n<p>Feature Forge\uff1a\u8fd9\u4e00\u7cfb\u5217\u5de5\u5177\u901a\u8fc7\u4e0escikit-learn\u517c\u5bb9\u7684API\uff0c\u6765\u521b\u5efa\u548c\u6d4b\u8bd5\u673a\u5668\u5b66\u4e60\u529f\u80fd\u3002\u8fd9\u4e2a\u5e93\u7a0b\u5e8f\u63d0\u4f9b\u4e86\u4e00\u7ec4\u5de5\u5177\uff0c\u5b83\u4f1a\u8ba9\u4f60\u5728\u8bb8\u591a\u673a\u5668\u5b66\u4e60\u7a0b\u5e8f\u4f7f\u7528\u4e2d\u5f88\u53d7\u7528\u3002\u5f53\u4f60\u4f7f\u7528scikit-learn\u8fd9\u4e2a\u5de5\u5177\u65f6\uff0c\u4f60\u4f1a\u611f\u89c9\u5230\u53d7\u5230\u4e86\u5f88\u5927\u7684\u5e2e\u52a9\u3002\uff08\u867d\u7136\u8fd9\u53ea\u80fd\u5728\u4f60\u4f7f\u7528\u4e0d\u540c\u7684\u7b97\u6cd5\u65f6\u8d77\u4f5c\u7528\u3002\uff09<\/p>\n<p>www.github.com\/machinalis\/featureforge<\/p>\n<p><strong>18<\/strong><\/p>\n<p>REP\uff1aREP\u662f\u4ee5\u4e00\u79cd\u548c\u8c10\u3001\u53ef\u518d\u751f\u7684\u65b9\u5f0f\u4e3a\u6307\u6325\u6570\u636e\u79fb\u52a8\u9a71\u52a8\u6240\u63d0\u4f9b\u7684\u4e00\u79cd\u73af\u5883\u3002\u5b83\u6709\u4e00\u4e2a\u7edf\u4e00\u7684\u5206\u7c7b\u5668\u5305\u88c5\u6765\u63d0\u4f9b\u5404\u79cd\u5404\u6837\u7684\u64cd\u4f5c\uff0c\u4f8b\u5982TMVA, Sklearn, XGBoost, uBoost\u7b49\u7b49\u3002\u5e76\u4e14\u5b83\u53ef\u4ee5\u5728\u4e00\u4e2a\u7fa4\u4f53\u4ee5\u5e73\u884c\u7684\u65b9\u5f0f\u8bad\u7ec3\u5206\u7c7b\u5668\u3002\u540c\u65f6\u5b83\u4e5f\u63d0\u4f9b\u4e86\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u7684\u60c5\u8282\u3002<\/p>\n<p>www.github.com\/yandex\/rep<\/p>\n<p><strong>19<\/strong><\/p>\n<p>Python 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