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2\u3001\u7b80\u6d01\u6613\u7528\u7684API<\/h4>\n<\/p>\n
PyTorch\u7684API\u8bbe\u8ba1\u7b80\u6d01\u660e\u4e86\uff0c\u6781\u5927\u964d\u4f4e\u4e86\u5b66\u4e60\u66f2\u7ebf\u3002\u5176\u4e0ePython\u7684\u9ad8\u5ea6\u96c6\u6210\u4f7f\u5f97\u5f00\u53d1\u8005\u53ef\u4ee5\u4f7f\u7528\u719f\u6089\u7684Python\u8bed\u6cd5\u8fdb\u884c\u5f00\u53d1\uff0c\u4ece\u800c\u63d0\u9ad8\u5f00\u53d1\u6548\u7387\u3002<\/p>\n<\/p>\n
\u4e09\u3001KERAS<\/h3>\n<\/p>\n
Keras\u662f\u4e00\u4e2a\u9ad8\u7ea7\u795e\u7ecf\u7f51\u7edcAPI\uff0c\u7531Python\u7f16\u5199\uff0c\u80fd\u591f\u5728TensorFlow\u3001CNTK\u548cTheano\u4e4b\u4e0a\u8fd0\u884c\u3002\u5b83\u7684\u8bbe\u8ba1\u7406\u5ff5\u662f\u7b80\u6d01\u6027\u548c\u53ef\u6269\u5c55\u6027\u3002<\/p>\n<\/p>\n
1\u3001\u7b80\u6d01\u6027<\/h4>\n<\/p>\n
Keras\u7684API\u975e\u5e38\u7b80\u6d01\uff0c\u5f00\u53d1\u8005\u53ea\u9700\u51e0\u884c\u4ee3\u7801\u5c31\u80fd\u6784\u5efa\u548c\u8bad\u7ec3\u4e00\u4e2a\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u3002\u8fd9\u4f7f\u5f97\u5b83\u6210\u4e3a\u521d\u5b66\u8005\u5b66\u4e60\u6df1\u5ea6\u5b66\u4e60\u7684\u7406\u60f3\u9009\u62e9\u3002<\/p>\n<\/p>\n
2\u3001\u53ef\u6269\u5c55\u6027<\/h4>\n<\/p>\n
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\u56db\u3001SCIKIT-LEARN<\/h3>\n<\/p>\n
Scikit-learn\u662f\u4e00\u4e2a\u57fa\u4e8ePython\u7684\u673a\u5668\u5b66\u4e60\u5e93\uff0c\u4e3b\u8981\u7528\u4e8e\u6570\u636e\u6316\u6398\u548c\u6570\u636e\u5206\u6790\u3002\u5b83\u5305\u542b\u4e86\u5927\u91cf\u7ecf\u5178\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u5982\u56de\u5f52\u3001\u5206\u7c7b\u548c\u805a\u7c7b\u3002<\/p>\n<\/p>\n
1\u3001\u4e30\u5bcc\u7684\u7b97\u6cd5\u5e93<\/h4>\n<\/p>\n
Scikit-learn\u5305\u542b\u4e86\u5927\u91cf\u7ecf\u5178\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u5f00\u53d1\u8005\u53ef\u4ee5\u8f7b\u677e\u8c03\u7528\u8fd9\u4e9b\u7b97\u6cd5\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u5efa\u6a21\u3002\u5b83\u8fd8\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u9884\u5904\u7406\u5de5\u5177\u548c\u6a21\u578b\u8bc4\u4f30\u65b9\u6cd5\uff0c\u4f7f\u5f97\u6574\u4e2a\u673a\u5668\u5b66\u4e60\u6d41\u7a0b\u53d8\u5f97\u66f4\u52a0\u6d41\u7545\u3002<\/p>\n<\/p>\n
2\u3001\u6613\u4e8e\u96c6\u6210<\/h4>\n<\/p>\n
Scikit-learn\u4e0e\u5176\u4ed6\u6570\u636e\u79d1\u5b66\u5e93\u5982NumPy\u3001SciPy\u548cPandas\u9ad8\u5ea6\u517c\u5bb9\uff0c\u5f00\u53d1\u8005\u53ef\u4ee5\u8f7b\u677e\u5c06\u5176\u96c6\u6210\u5230\u73b0\u6709\u7684\u6570\u636e\u79d1\u5b66\u5de5\u4f5c\u6d41\u7a0b\u4e2d\u3002\u8fd9\u4f7f\u5f97\u5b83\u6210\u4e3a\u6570\u636e\u5206\u6790\u548c\u5efa\u6a21\u7684\u5e38\u7528\u5de5\u5177\u3002<\/p>\n<\/p>\n
\u4e94\u3001MICROSOFT COGNITIVE TOOLKIT (CNTK)<\/h3>\n<\/p>\n
Microsoft Cognitive Toolkit\uff08CNTK\uff09\u662f\u5fae\u8f6f\u5f00\u53d1\u7684\u4e00\u4e2a\u5f00\u6e90\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0c\u4e3b\u8981\u7528\u4e8e\u6784\u5efa\u548c\u8bad\u7ec3\u795e\u7ecf\u7f51\u7edc\u3002<\/p>\n<\/p>\n
1\u3001\u9ad8\u6548\u7684\u8ba1\u7b97\u6027\u80fd<\/h4>\n<\/p>\n
CNTK\u91c7\u7528\u4e86\u9ad8\u6548\u7684\u8ba1\u7b97\u56fe\u5f15\u64ce\uff0c\u80fd\u591f\u5728\u591a\u4e2aGPU\u548cCPU\u4e0a\u9ad8\u6548\u8fd0\u884c\u3002\u8fd9\u4f7f\u5f97\u5b83\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u548c\u590d\u6742\u6a21\u578b\u65f6\u8868\u73b0\u5f97\u5c24\u4e3a\u51fa\u8272\u3002<\/p>\n<\/p>\n
2\u3001\u4e30\u5bcc\u7684\u529f\u80fd<\/h4>\n<\/p>\n
CNTK\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u5982\u81ea\u52a8\u5fae\u5206\u3001\u5e76\u884c\u8bad\u7ec3\u548c\u6a21\u578b\u8bc4\u4f30\uff0c\u4f7f\u5f97\u5f00\u53d1\u8005\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u590d\u6742\u7684\u6df1\u5ea6\u5b66\u4e60\u4efb\u52a1\u3002\u5b83\u8fd8\u652f\u6301\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00\uff0c\u5982Python\u3001C++\u548cC#\uff0c\u63d0\u9ad8\u4e86\u5f00\u53d1\u7684\u7075\u6d3b\u6027\u3002<\/p>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
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TensorFlow<\/strong>\u9002\u5408\u9700\u8981\u9ad8\u6027\u80fd\u8ba1\u7b97\u548c\u590d\u6742\u6a21\u578b\u7684\u9879\u76ee\uff0cPyTorch<\/strong>\u5219\u4ee5\u5176\u52a8\u6001\u8ba1\u7b97\u56fe\u548c\u7b80\u6d01\u6613\u7528\u7684API\u5438\u5f15\u4e86\u5927\u91cf\u7814\u7a76\u4eba\u5458\u548c\u5f00\u53d1\u8005\u3002Keras<\/strong>\u63d0\u4f9b\u4e86\u7b80\u6d01\u7684API\uff0c\u975e\u5e38\u9002\u5408\u521d\u5b66\u8005\u548c\u5feb\u901f\u539f\u578b\u5f00\u53d1\u3002Scikit-learn<\/strong>\u5305\u542b\u4e86\u4e30\u5bcc\u7684\u7ecf\u5178\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u662f\u6570\u636e\u5206\u6790\u548c\u5efa\u6a21\u7684\u5e38\u7528\u5de5\u5177\u3002Microsoft Cognitive Toolkit (CNTK)\u5219\u4ee5\u5176\u9ad8\u6548\u7684\u8ba1\u7b97\u6027\u80fd\u548c\u4e30\u5bcc\u7684\u529f\u80fd\u5728\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u8868\u73b0\u51fa\u8272\u3002<\/p>\n<\/p>\n\u901a\u8fc7\u5bf9\u8fd9\u4e9b\u7cfb\u7edf\u7684\u4e86\u89e3\u548c\u6bd4\u8f83\uff0c\u5f00\u53d1\u8005\u53ef\u4ee5\u66f4\u597d\u5730\u9009\u62e9\u548c\u4f7f\u7528\u4eba\u5de5\u667a\u80fd\u5f00\u53d1\u7cfb\u7edf\uff0c\u4ece\u800c\u5b9e\u73b0\u9ad8\u6548\u3001\u51c6\u786e\u7684AI\u6a21\u578b\u3002<\/p>\n<\/p>\n
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