{"id":189447,"date":"2024-05-09T17:37:56","date_gmt":"2024-05-09T09:37:56","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/189447.html"},"modified":"2024-05-09T17:38:01","modified_gmt":"2024-05-09T09:38:01","slug":"%e6%9c%89%e5%93%aa%e4%ba%9b%e6%af%94%e8%be%83%e5%a5%bd%e7%9a%84%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%ef%bc%8c%e6%b7%b1%e5%ba%a6%e5%ad%a6%e4%b9%a0%e7%9a%84%e7%bd%91%e7%bb%9c%e8%b5%84%e6%ba%90%e5%8f%af","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/189447.html","title":{"rendered":"\u6709\u54ea\u4e9b\u6bd4\u8f83\u597d\u7684\u673a\u5668\u5b66\u4e60\uff0c\u6df1\u5ea6\u5b66\u4e60\u7684\u7f51\u7edc\u8d44\u6e90\u53ef\u5229\u7528"},"content":{"rendered":"

\"\u6709\u54ea\u4e9b\u6bd4\u8f83\u597d\u7684\u673a\u5668\u5b66\u4e60\uff0c\u6df1\u5ea6\u5b66\u4e60\u7684\u7f51\u7edc\u8d44\u6e90\u53ef\u5229\u7528\"<\/p>\n

\u673a\u5668\u5b66\u4e60<\/a>\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u9886\u57df\u53d1\u5c55\u8fc5\u731b\u3001\u9ad8\u6821\u8bfe\u7a0b\u3001\u5728\u7ebf\u8bfe\u7a0b\u5e73\u53f0\u3001\u5f00\u653e\u6e90\u4ee3\u7801\u5e93\u3001\u4e13\u4e1a\u793e\u533a\u4ee5\u53ca\u5b66\u672f\u4f1a\u8bae\u7b49\u8d44\u6e90<\/strong>\u6781\u5927\u5730\u65b9\u4fbf\u4e86\u5b66\u4e60\u8fd9\u4e00\u9886\u57df\u7684\u4e13\u4e1a\u4eba\u58eb\u548c\u7231\u597d\u8005\u3002<\/p>\n<\/p>\n

\u9ad8\u6821\u8bfe\u7a0b\u7ecf\u5e38\u63d0\u4f9b\u7406\u8bba\u57fa\u7840\u548c\u6280\u672f\u7ec6\u8282\u65b9\u9762\u7684\u624e\u5b9e\u77e5\u8bc6\u3002\u4f8b\u5982\uff0c\u65af\u5766\u798f\u5927\u5b66\u7684Andrew Ng\u6559\u6388\u7684\u673a\u5668\u5b66\u4e60\u8bfe\u7a0b\uff0c\u5df2\u6210\u4e3a\u5165\u95e8\u8005\u7684\u5fc5\u5b66\u8bfe\u7a0b\u3002\u5728\u7ebf\u8bfe\u7a0b\u5e73\u53f0\uff0c\u5982Coursera\u3001Udacity\u548cedX\uff0c\u63d0\u4f9b\u4e86\u591a\u79cd\u4e0e\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u76f8\u5173\u7684\u8bfe\u7a0b\uff0c\u7531\u4e16\u754c\u5404\u5730\u7684\u4e13\u5bb6\u6559\u6388\u6388\u8bfe\u3002\u8fd9\u4e9b\u8bfe\u7a0b\u5f80\u5f80\u7ed3\u5408\u4e86\u89c6\u9891\u8bb2\u5ea7\u3001\u9605\u8bfb\u6750\u6599\u3001\u8f6f\u4ef6\u5de5\u5177\u7684\u5b9e\u64cd\u548c\u8ba8\u8bba\u8bba\u575b\u3002\u5f00\u653e\u6e90\u4ee3\u7801\u5e93<\/strong>\u5982TensorFlow\u3001PyTorch\u548cScikit-learn\uff0c\u4e0d\u4ec5\u53ef\u4f9b\u5b66\u4e60\u8005\u8fdb\u884c\u5b9e\u8df5\uff0c\u4e5f\u662f\u7814\u7a76\u4eba\u5458\u548c\u4ece\u4e1a\u8005\u65e5\u5e38\u5de5\u4f5c\u4e2d\u4e0d\u53ef\u6216\u7f3a\u7684\u5de5\u5177\u3002\u4e13\u4e1a\u793e\u533a<\/strong>\u6bd4\u5982Kaggle\u3001GitHub\u548cStack Overflow\uff0c\u4e3a\u5b66\u4e60\u8005\u63d0\u4f9b\u4e86\u6570\u636e\u96c6\u3001\u9879\u76ee\u3001\u6280\u672f\u4ea4\u6d41\u548c\u89e3\u51b3\u95ee\u9898\u7684\u573a\u6240\u3002\u5b66\u672f\u4f1a\u8bae<\/strong>\u5982NeurIPS\u3001ICML\u548cCVPR\uff0c\u5219\u662f\u8fd9\u4e00\u9886\u57df\u6700\u65b0\u7814\u7a76\u6210\u679c\u548c\u672a\u6765\u8d8b\u52bf\u7684\u98ce\u5411\u6807\u3002<\/p>\n<\/p>\n

\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5404\u79cd\u9ad8\u8d28\u91cf\u7684\u7f51\u7edc\u8d44\u6e90\uff0c\u5e76\u8bf4\u660e\u5982\u4f55\u5229\u7528\u8fd9\u4e9b\u8d44\u6e90\u8fdb\u884c\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u5b66\u4e60\u548c\u7814\u7a76\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5f00\u653e\u6e90\u4ee3\u7801\u5e93<\/p>\n<\/p>\n

\u5f00\u6e90\u4ee3\u7801\u5e93<\/strong> \u5bf9\u4e8e\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u5b66\u4e60\u548c\u7814\u7a76\u5177\u6709\u91cd\u8981\u610f\u4e49\u3002\u5b83\u4eec\u4e0d\u4ec5\u63d0\u4f9b\u4e86\u4e00\u5957\u529f\u80fd\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u800c\u4e14\u901a\u5e38\u4f34\u968f\u6709\u5e7f\u6cdb\u7684\u6587\u6863\u548c\u793e\u533a\u652f\u6301\u3002<\/p>\n<\/p>\n

    \n
  1. \n

    TensorFlow<\/p>\n

    \u7531\u8c37\u6b4c\u5f00\u53d1\u7684TensorFlow\u662f\u5f53\u524d\u6700\u53d7\u6b22\u8fce\u7684\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u4e4b\u4e00\u3002\u5b83\u4e0d\u4ec5\u9002\u5408\u7814\u7a76\u548c\u53d1\u5c55\u5b9e\u9a8c\u6027\u9879\u76ee\uff0c\u4e5f\u80fd\u5904\u7406\u5927\u89c4\u6a21\u7684\u673a\u5668\u5b66\u4e60\u5e94\u7528\u3002TensorFlow\u652f\u6301\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00\uff0c\u5177\u6709\u7075\u6d3b\u6027\u548c\u6a21\u5757\u5316\uff0c\u4f7f\u5f97\u60a8\u53ef\u4ee5\u8f7b\u677e\u6784\u5efa\u548c\u90e8\u7f72\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002<\/p>\n<\/p>\n<\/li>\n

  2. \n

    PyTorch<\/p>\n

    \u7531Facebook\u7684AI<\/a>\u7814\u7a76\u56e2\u961f\u5f00\u53d1\u7684PyTorch\u4ee5\u5176\u76f4\u89c2\u6613\u7528\u548c\u52a8\u6001\u8ba1\u7b97\u56fe\u800c\u53d7\u5230\u7814\u7a76\u4eba\u5458\u7684\u9752\u7750\u3002\u5176\u7b80\u6d01\u7684\u8bbe\u8ba1\u548c\u7075\u6d3b\u6027\u8ba9\u7814\u7a76\u548c\u5b9e\u9a8c\u8fc7\u7a0b\u66f4\u52a0\u9ad8\u6548\u3002\u6b64\u5916\uff0cPyTorch\u62e5\u6709\u4e00\u4e2a\u6d3b\u8dc3\u7684\u793e\u533a\uff0c\u4e30\u5bcc\u7684\u5b66\u4e60\u8d44\u6e90\u548c\u6269\u5f20\u5e93\u4f7f\u5f97\u5176\u5728\u5b66\u672f\u754c\u8d8a\u6765\u8d8a\u53d7\u6b22\u8fce\u3002<\/p>\n<\/p>\n<\/li>\n

  3. \n

    Scikit-learn<\/p>\n

    Scikit-learn\u662f\u4e00\u4e2aPython\u7f16\u7a0b\u8bed\u8a00\u7684\u5f00\u653e\u6e90\u4ee3\u7801\u673a\u5668\u5b66\u4e60\u5e93\u3002\u5b83\u9002\u5408\u4e8e\u6267\u884c\u5404\u79cd\u673a\u5668\u5b66\u4e60\u4efb\u52a1\uff0c\u5305\u62ec\u5206\u7c7b\u3001\u56de\u5f52\u3001\u805a\u7c7b\u548c\u964d\u7ef4\u3002Scikit-learn\u5e93\u7684\u4f18\u70b9\u662f\u4ee3\u7801\u8d28\u91cf\u9ad8\u3001\u6587\u6863\u9f50\u5168\u3001\u5b66\u4e60\u66f2\u7ebf\u5e73\u7f13\uff0c\u9002\u5408\u521d\u5b66\u8005\u5feb\u901f\u5165\u95e8\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

    \u4e8c\u3001\u5728\u7ebf\u8bfe\u7a0b\u548c\u6559\u80b2\u5e73\u53f0<\/p>\n<\/p>\n

    \u5728\u7ebf\u5b66\u4e60\u5e73\u53f0\u4f7f\u5f97\u5b66\u4e60\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u53d8\u5f97\u66f4\u52a0\u7075\u6d3b\u548c\u65b9\u4fbf\uff0c\u8fd9\u4e9b\u8d44\u6e90\u901a\u5e38\u5305\u62ec\u8bb2\u5ea7\u89c6\u9891\u3001\u9605\u8bfb\u6750\u6599\u3001\u9879\u76ee\u4f5c\u4e1a\u548c\u8003\u8bd5\u3002<\/p>\n<\/p>\n

      \n
    1. \n

      Coursera<\/p>\n

      Coursera\u5e73\u53f0\u4e0a\u6709\u591a\u95e8\u7531\u9876\u7ea7\u5927\u5b66\u548c\u884c\u4e1a\u4e13\u5bb6\u5f00\u8bbe\u7684\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u8bfe\u7a0b\u3002\u65af\u5766\u798f\u5927\u5b66\u7684Andrew Ng\u6559\u6388\u5f00\u8bbe\u7684\u201c\u673a\u5668\u5b66\u4e60\u201d\u8bfe\u7a0b\u548cDeepLearning.AI\u63a8\u51fa\u7684\u6df1\u5ea6\u5b66\u4e60\u4e13\u9879\u8bfe\u7a0b\u90fd\u662f\u8be5\u5e73\u53f0\u7684\u660e\u661f\u8bfe\u7a0b\u3002<\/p>\n<\/p>\n<\/li>\n

    2. \n

      Udacity<\/p>\n

      Udacity\u7684\u201c\u7eb3\u7c73\u5b66\u4f4d\u7a0b\u5e8f\u201d\u7ed3\u5408\u4e86\u6559\u80b2\u548c\u804c\u4e1a\u57f9\u8bad\u3002\u5b83\u4eec\u63d0\u4f9b\u4e13\u95e8\u81f4\u529b\u4e8e\u4eba\u5de5\u667a\u80fd<\/a>\u3001\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u8bfe\u7a0b\uff0c\u6d89\u53ca\u7406\u8bba\u5b66\u4e60\u548c\u9879\u76ee\u5b9e\u8df5\uff0c\u5e76\u4e14\u6709\u884c\u4e1a\u4e13\u5bb6\u63d0\u4f9b\u53cd\u9988\u3002<\/p>\n<\/p>\n<\/li>\n

    3. \n

      edX<\/p>\n

      \u7531\u54c8\u4f5b\u5927\u5b66\u548c\u9ebb\u7701\u7406\u5de5\u5b66\u9662\u5171\u540c\u521b\u7acb\u7684edX\u5e73\u53f0\uff0c\u4e3a\u5b66\u4e60\u8005\u63d0\u4f9b\u4e86\u5305\u62ec\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u5728\u5185\u7684\u591a\u79cd\u79d1\u6280\u548c\u7f16\u7a0b\u76f8\u5173\u8bfe\u7a0b\u3002 \u8fd9\u4e9b\u8bfe\u7a0b\u901a\u5e38\u662f\u81ea\u5b66\u578b\u7684\uff0c\u5e76\u63d0\u4f9b\u8bc1\u4e66\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

      \u4e09\u3001\u4e13\u4e1a\u5b66\u4e60\u793e\u533a\u548c\u7ade\u8d5b\u5e73\u53f0<\/p>\n<\/p>\n

      \u52a0\u5165\u4e13\u4e1a\u793e\u533a\u548c\u53c2\u4e0e\u7ade\u8d5b\u53ef\u4ee5\u8ba9\u5b66\u4e60\u8005\u66f4\u597d\u5730\u5b9e\u8df5\u6240\u5b66\uff0c\u5e76\u4e0e\u540c\u884c\u4ea4\u6d41\u5206\u4eab\u3002<\/p>\n<\/p>\n

        \n
      1. \n

        Kaggle<\/p>\n

        Kaggle\u662f\u4e00\u4e2a\u8457\u540d\u7684\u6570\u636e\u79d1\u5b66\u7ade\u8d5b\u5e73\u53f0\uff0c\u7528\u6237\u53ef\u4ee5\u5728\u6b64\u53c2\u52a0\u5404\u79cd\u673a\u5668\u5b66\u4e60\u6311\u6218\uff0c\u89e3\u51b3\u73b0\u5b9e\u4e16\u754c\u7684\u95ee\u9898\u3002\u9664\u4e86\u7ade\u8d5b\uff0cKaggle\u8fd8\u63d0\u4f9b\u516c\u5f00\u7684\u6570\u636e\u96c6\u3001Kernels\uff08\u5373\u4e4b\u524d\u7684\u811a\u672c\u6216\u5206\u6790\uff09\u3001\u4ee5\u53ca\u8bba\u575b\uff0c\u662f\u4fe1\u606f\u4ea4\u6d41\u548c\u5b66\u4e60\u7684\u597d\u53bb\u5904\u3002<\/p>\n<\/p>\n<\/li>\n

      2. \n

        GitHub<\/p>\n

        GitHub\u662f\u5168\u7403\u6700\u5927\u7684\u4ee3\u7801\u6258\u7ba1\u5e73\u53f0\uff0c\u5f00\u53d1\u8005\u53ef\u4ee5\u5728\u6b64\u627e\u5230\u65e0\u6570\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u9879\u76ee\u3002\u53c2\u4e0e\u8fd9\u4e9b\u9879\u76ee\u4e0d\u4ec5\u53ef\u4ee5\u63d0\u9ad8\u7f16\u7a0b\u6280\u80fd\uff0c\u8fd8\u80fd\u5b66\u4e60\u5230\u5982\u4f55\u534f\u4f5c\u548c\u5de5\u4f5c\u6d41\u7a0b\u7ba1\u7406\u3002<\/p>\n<\/p>\n<\/li>\n

      3. \n

        Stack Overflow<\/p>\n

        Stack Overflow\u662f\u7a0b\u5e8f\u5458\u89e3\u51b3\u7f16\u7a0b\u95ee\u9898\u7684\u9996\u9009\u7f51\u7ad9\u3002\u5728\u8fd9\u91cc\uff0c\u4f60\u53ef\u4ee5\u5411\u5176\u4ed6\u5f00\u53d1\u8005\u63d0\u95ee\u6216\u5e2e\u52a9\u89e3\u7b54\u4e0e\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u76f8\u5173\u7684\u6280\u672f\u95ee\u9898\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

        \u56db\u3001\u5b66\u672f\u4f1a\u8bae\u548c\u671f\u520a<\/p>\n<\/p>\n

        \u5b66\u672f\u4f1a\u8bae\u548c\u671f\u520a\u662f\u83b7\u53d6\u6700\u65b0\u7814\u7a76\u6210\u679c\u7684\u4e3b\u8981\u6e20\u9053\u3002<\/p>\n<\/p>\n

          \n
        1. \n

          NeurIPS\uff08National Conference on Neural Information Processing Systems\uff09<\/p>\n

          NeurIPS\u662f\u4eba\u5de5\u667a\u80fd\u548c\u673a\u5668\u5b66\u4e60\u9886\u57df\u7684\u9876\u7ea7\u4f1a\u8bae\u4e4b\u4e00\uff0c\u6bcf\u5e74\u53d1\u5e03\u5f88\u591a\u521b\u65b0\u7814\u7a76\u8bba\u6587\u548c\u6700\u65b0\u6280\u672f\u8fdb\u5c55\u3002<\/p>\n<\/p>\n<\/li>\n

        2. \n

          ICML\uff08International Conference on Machine Learning\uff09<\/p>\n

          ICML\u662f\u53e6\u4e00\u4e2a\u91cd\u8981\u7684\u673a\u5668\u5b66\u4e60\u4f1a\u8bae\uff0c\u56f4\u7ed5\u673a\u5668\u5b66\u4e60\u7684\u7406\u8bba\u3001\u7b97\u6cd5\u548c\u5e94\u7528\u5c55\u5f00\u7814\u7a76\u548c\u8ba8\u8bba\u3002<\/p>\n<\/p>\n<\/li>\n

        3. \n

          CVPR\uff08Conference on Computer Vision and Pattern Recognition\uff09<\/p>\n

          CVPR\u662f\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u6a21\u5f0f\u8bc6\u522b\u9886\u57df\u7684\u6700\u91cd\u8981\u4f1a\u8bae\u4e4b\u4e00\uff0c\u6d89\u53ca\u8bb8\u591a\u6df1\u5ea6\u5b66\u4e60\u76f8\u5173\u7684\u5185\u5bb9\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

          \u4e94\u3001\u5176\u4ed6\u8d44\u6e90<\/p>\n<\/p>\n

          \u9664\u4e86\u4e0a\u8ff0\u91cd\u70b9\u4ecb\u7ecd\u7684\u8d44\u6e90\u5916\uff0c\u8fd8\u6709\u4e00\u4e9b\u5176\u4ed6\u53ef\u7528\u7684\u5de5\u5177\u548c\u5e73\u53f0\uff0c\u53ef\u4ee5\u5e2e\u52a9\u5b66\u4e60\u8005\u8fdb\u4e00\u6b65\u62d3\u5c55\u81ea\u5df1\u7684\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u77e5\u8bc6\uff0c\u4f8b\u5982\u8c37\u6b4c\u7684Colab\u3001FAST.AI\u4ee5\u53ca\u5404\u7c7b\u79d1\u6280\u535a\u5ba2\u548cYouTube\u9891\u9053\u3002<\/p>\n<\/p>\n

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