{"id":56693,"date":"2025-08-14T22:14:32","date_gmt":"2025-08-14T14:14:32","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/56693.html"},"modified":"2025-08-14T22:14:32","modified_gmt":"2025-08-14T14:14:32","slug":"%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%e5%b8%b8%e7%94%a8python%e5%ba%93%e5%8f%8a%e5%85%b6%e5%ba%94%e7%94%a8%e5%9c%ba%e6%99%af","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/56693.html","title":{"rendered":"\u673a\u5668\u5b66\u4e60\u5e38\u7528Python\u5e93\u53ca\u5176\u5e94\u7528\u573a\u666f"},"content":{"rendered":"

1. \u6838\u5fc3\u6570\u503c\u8ba1\u7b97\u4e0e\u6570\u636e\u5904\u7406<\/span><\/p>\n

NumPy<\/span>：\u63d0\u4f9b\u9ad8\u6027\u80fd\u7684\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\u548c\u6570\u5b66\u51fd\u6570，\u662f\u51e0\u4e4e\u6240\u6709\u673a\u5668\u5b66\u4e60\u5e93\u7684\u57fa\u7840，\u7528\u4e8e\u6570\u503c\u8ba1\u7b97\u3001\u77e9\u9635\u8fd0\u7b97\u7b49\u5e95\u5c42\u64cd\u4f5c\u3002<\/p>\n

Pandas<\/span>：\u4e13\u6ce8\u4e8e\u7ed3\u6784\u5316\u6570\u636e\u5904\u7406，\u63d0\u4f9b DataFrame \u6570\u636e\u7ed3\u6784，\u65b9\u4fbf\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3001\u8f6c\u6362\u3001\u805a\u5408\u548c\u5206\u6790，\u662f\u6570\u636e\u9884\u5904\u7406\u7684\u6838\u5fc3\u5de5\u5177\u3002<\/p>\n

2. \u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u5e93<\/span><\/p>\n

Scikit-learn<\/span>：\u5305\u542b\u4e86\u51e0\u4e4e\u6240\u6709\u7ecf\u5178\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5（\u5982\u7ebf\u6027\u56de\u5f52\u3001\u51b3\u7b56\u6811\u3001SVM\u3001\u968f\u673a\u68ee\u6797\u3001K-Means \u7b49），\u63d0\u4f9b\u7edf\u4e00\u7684 API \u63a5\u53e3，\u652f\u6301\u6570\u636e\u5206\u5272\u3001\u7279\u5f81\u9009\u62e9\u3001\u6a21\u578b\u8bc4\u4f30\u7b49\u5b8c\u6574\u6d41\u7a0b，\u9002\u5408\u5feb\u901f\u6784\u5efa\u57fa\u7ebf\u6a21\u578b\u548c\u4e2d\u5c0f\u578b\u9879\u76ee\u3002<\/p>\n

XGBoost\/LightGBM\/CatBoost<\/span>：\u9ad8\u6027\u80fd\u7684\u68af\u5ea6\u63d0\u5347\u6811\u5e93，\u5728\u5206\u7c7b\u3001\u56de\u5f52\u7b49\u4efb\u52a1\u4e2d\u8868\u73b0\u4f18\u5f02，\u5c24\u5176\u9002\u5408\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e，\u5e38\u7528\u4e8e\u7ade\u8d5b\u548c\u5de5\u4e1a\u754c\u3002<\/p>\n

3. \u6df1\u5ea6\u5b66\u4e60\u6846\u67b6<\/p>\n

TensorFlow<\/span>：\u7531 Google \u5f00\u53d1\u7684\u5f00\u6e90\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6，\u652f\u6301\u9759\u6001\u8ba1\u7b97\u56fe，\u9002\u5408\u6784\u5efa\u590d\u6742\u7684\u795e\u7ecf\u7f51\u7edc\u6a21\u578b（\u5982 CNN\u3001RNN\u3001Transformer \u7b49），\u6269\u5c55\u6027\u5f3a，\u9002\u5408\u751f\u4ea7\u73af\u5883\u90e8\u7f72\u3002<\/p>\n

PyTorch<\/span>：\u7531 Facebook \u5f00\u53d1，\u91c7\u7528\u52a8\u6001\u8ba1\u7b97\u56fe，\u7075\u6d3b\u6027\u9ad8，\u8c03\u8bd5\u65b9\u4fbf，\u66f4\u53d7\u5b66\u672f\u754c\u9752\u7750，\u9002\u5408\u5feb\u901f\u539f\u578b\u5f00\u53d1\u548c\u7814\u7a76\u3002<\/p>\n

Keras<\/span>：\u57fa\u4e8e TensorFlow\/PyTorch \u7b49\u540e\u7aef\u7684\u9ad8\u5c42\u795e\u7ecf\u7f51\u7edc API，\u8bed\u6cd5\u7b80\u6d01，\u9002\u5408\u5feb\u901f\u642d\u5efa\u548c\u8bad\u7ec3\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b，\u5bf9\u521d\u5b66\u8005\u53cb\u597d\u3002<\/p>\n

4. \u6570\u636e\u53ef\u89c6\u5316<\/span><\/p>\n

Matplotlib<\/span>：\u57fa\u7840\u7684\u7ed8\u56fe\u5e93，\u652f\u6301\u7ebf\u56fe\u3001\u6563\u70b9\u56fe\u3001\u76f4\u65b9\u56fe\u7b49\u591a\u79cd\u56fe\u8868，\u53ef\u9ad8\u5ea6\u5b9a\u5236\u5316，\u9002\u5408\u751f\u6210 publication \u7ea7\u522b\u7684\u56fe\u5f62\u3002<\/p>\n

Seaborn<\/span>：\u57fa\u4e8e Matplotlib，\u63d0\u4f9b\u66f4\u7f8e\u89c2\u7684\u9ed8\u8ba4\u6837\u5f0f\u548c\u9ad8\u7ea7\u7edf\u8ba1\u7ed8\u56fe\u529f\u80fd（\u5982\u70ed\u56fe\u3001\u5c0f\u63d0\u7434\u56fe），\u9002\u5408\u6570\u636e\u5206\u5e03\u548c\u5173\u7cfb\u7684\u53ef\u89c6\u5316\u3002<\/p>\n

Plotly<\/span>：\u652f\u6301\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316，\u53ef\u751f\u6210\u52a8\u6001\u56fe\u8868\u30013D \u56fe\u5f62\u7b49，\u9002\u5408\u6784\u5efa\u4eea\u8868\u76d8\u548c Web \u5e94\u7528\u4e2d\u7684\u53ef\u89c6\u5316\u7ec4\u4ef6\u3002<\/p>\n

5. \u81ea\u7136\u8bed\u8a00\u5904\u7406（NLP）<\/span><\/p>\n

NLTK<\/span>：\u81ea\u7136\u8bed\u8a00\u5904\u7406\u57fa\u7840\u5e93，\u5305\u542b\u8bed\u6599\u5e93\u3001\u5206\u8bcd\u3001\u8bcd\u6027\u6807\u6ce8\u3001\u53e5\u6cd5\u5206\u6790\u7b49\u5de5\u5177，\u9002\u5408\u5165\u95e8\u5b66\u4e60\u3002<\/p>\n

SpaCy<\/span>：\u5de5\u4e1a\u7ea7 NLP \u5e93，\u652f\u6301\u9ad8\u6548\u7684\u5206\u8bcd\u3001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b（NER）\u3001\u4f9d\u5b58\u53e5\u6cd5\u5206\u6790\u7b49，\u6a21\u578b\u8bad\u7ec3\u548c\u90e8\u7f72\u4fbf\u6377\u3002<\/p>\n

Hugging Face Transformers<\/span>：\u63d0\u4f9b\u5927\u91cf\u9884\u8bad\u7ec3\u7684 NLP \u6a21\u578b（\u5982 BERT\u3001GPT\u3001T5 \u7b49），\u652f\u6301\u6587\u672c\u5206\u7c7b\u3001\u7ffb\u8bd1\u3001\u6458\u8981\u7b49\u4efb\u52a1，\u5f00\u7bb1\u5373\u7528\u3002<\/p>\n

6. \u8ba1\u7b97\u673a\u89c6\u89c9（CV）<\/span><\/p>\n

OpenCV<\/span>：\u5f00\u6e90\u8ba1\u7b97\u673a\u89c6\u89c9\u5e93，\u652f\u6301\u56fe\u50cf\u8bfb\u53d6\u3001\u9884\u5904\u7406\u3001\u7279\u5f81\u63d0\u53d6\u3001\u76ee\u6807\u68c0\u6d4b\u7b49，\u5e7f\u6cdb\u5e94\u7528\u4e8e\u5b9e\u65f6\u56fe\u50cf\u5904\u7406\u3002<\/p>\n

Pillow<\/span>：Python \u56fe\u50cf\u5904\u7406\u5e93，\u63d0\u4f9b\u56fe\u50cf\u6253\u5f00\u3001\u88c1\u526a\u3001\u65cb\u8f6c\u3001\u6ee4\u955c\u7b49\u57fa\u672c\u64cd\u4f5c，\u63a5\u53e3\u7b80\u5355\u6613\u7528\u3002<\/p>\n

TorchVision\/TensorFlow Datasets<\/span>：\u5206\u522b\u4e0e PyTorch\u3001TensorFlow \u914d\u5957，\u5305\u542b\u5e38\u7528\u7684 CV \u6570\u636e\u96c6（\u5982 MNIST\u3001CIFAR-10）\u548c\u9884\u8bad\u7ec3\u6a21\u578b（\u5982 ResNet\u3001VGG）\u3002<\/p>\n

7. \u6a21\u578b\u90e8\u7f72\u4e0e\u4f18\u5316<\/span><\/p>\n

ONNX<\/span>：\u5f00\u653e\u795e\u7ecf\u7f51\u7edc\u4ea4\u6362\u683c\u5f0f，\u5b9e\u73b0\u4e0d\u540c\u6846\u67b6\u95f4\u7684\u6a21\u578b\u8f6c\u6362（\u5982 PyTorch \u8f6c TensorFlow），\u4fbf\u4e8e\u8de8\u5e73\u53f0\u90e8\u7f72\u3002<\/p>\n

TensorRT<\/span>：NVIDIA \u7684\u6df1\u5ea6\u5b66\u4e60\u63a8\u7406\u4f18\u5316\u5668，\u53ef\u52a0\u901f\u6a21\u578b\u5728 GPU \u4e0a\u7684\u63a8\u7406\u901f\u5ea6，\u9002\u5408\u751f\u4ea7\u73af\u5883\u90e8\u7f72\u3002<\/p>\n

Flask\/FastAPI<\/span>：\u8f7b\u91cf\u7ea7 Web \u6846\u67b6，\u7528\u4e8e\u5c06\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u5c01\u88c5\u4e3a API \u670d\u52a1，\u5b9e\u73b0\u6a21\u578b\u7684\u5728\u7ebf\u8c03\u7528\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

\u6587\u7ae0\u6d4f\u89c8\u9605\u8bfb21\u6b21\u3002\u5305\u542b\u4e86\u51e0\u4e4e\u6240\u6709\u7ecf\u5178\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff08\u5982\u7ebf\u6027\u56de\u5f52\u3001\u51b3\u7b56\u6811\u3001SVM\u3001\u968f\u673a\u68ee\u6797\u3001K-Means \u7b49\uff09\uff0c\u63d0\u4f9b\u7edf\u4e00\u7684 API \u63a5\u53e3\uff0c\u652f\u6301\u6570\u636e\u5206\u5272\u3001\u7279\u5f81\u9009\u62e9\u3001\u6a21\u578b\u8bc4\u4f30\u7b49\u5b8c\u6574\u6d41\u7a0b\uff0c\u9002\u5408\u5feb\u901f\u6784\u5efa\u57fa\u7ebf\u6a21\u578b\u548c\u4e2d\u5c0f\u578b\u9879\u76ee\u3002\uff1a\u7531 Google \u5f00\u53d1\u7684\u5f00\u6e90\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0c\u652f\u6301\u9759\u6001\u8ba1\u7b97\u56fe\uff0c\u9002\u5408\u6784\u5efa\u590d\u6742\u7684\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\uff08\u5982 CNN\u3001RNN\u3001Transformer \u7b49\uff09\uff0c\u6269\u5c55\u6027\u5f3a\uff0c\u9002\u5408\u751f\u4ea7\u73af\u5883\u90e8\u7f72\u3002\uff1a\u63d0\u4f9b\u5927\u91cf\u9884\u8bad\u7ec3\u7684 NLP \u6a21\u578b\uff08\u5982 BERT\u3001GPT\u3001T5 \u7b49\uff09\uff0c\u652f\u6301\u6587\u672c\u5206\u7c7b\u3001\u7ffb\u8bd1\u3001\u6458\u8981\u7b49\u4efb\u52a1\uff0c\u5f00\u7bb1\u5373\u7528\u3002<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[81,50,5913,4162,207],"topic":[],"class_list":["post-56693","post","type-post","status-publish","format-standard","hentry","category-server","tag-python","tag-50","tag-5913","tag-4162","tag-207"],"yoast_head":"\n\u673a\u5668\u5b66\u4e60\u5e38\u7528Python\u5e93\u53ca\u5176\u5e94\u7528\u573a\u666f - 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