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01.1.人工智能学习方法.mp4 | 2023-12-31 05:45:20 | 405.89 MB |
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02.2-机器学习的距离.mp4 | 2023-12-31 05:45:20 | 434.24 MB |
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03.3.线性回归.mp4 | 2023-12-31 05:45:20 | 455.65 MB |
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04.4深入理解线性回归.mp4 | 2023-12-31 05:45:20 | 509.53 MB |
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05.5逻辑回归原理和入门mp4.mp4 | 2023-12-31 05:45:20 | 503.98 MB |
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06.6深入理解逻辑回归.mp4 | 2023-12-31 05:45:20 | 402.89 MB |
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07.7逻辑回归正则项和上下采样.mp4 | 2023-12-31 05:45:20 | 492.67 MB |
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08.8FM模型_嗨格式压缩副本.mp4 | 2023-12-31 05:45:20 | 319.53 MB |
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09.9.分类模型的数学原理.mp4 | 2023-12-31 05:45:20 | 517.03 MB |
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10.10聚类模型kmeans.mp4 | 2023-12-31 05:45:20 | 487.71 MB |
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11.11深入理解kmeans.mp4 | 2023-12-31 05:45:20 | 481.06 MB |
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12.12深度学习入门.mp4 | 2023-12-31 05:45:20 | 236.04 MB |
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13.13keras和TensorFlow实战.mp4 | 2023-12-31 05:45:20 | 472.41 MB |
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14.14神经网络的梯度下降法_嗨格式压缩副本.mp4 | 2023-12-31 05:45:20 | 495.13 MB |
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15.15矩阵求导术.mp4 | 2023-12-31 05:45:20 | 486.34 MB |
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16.16矩阵求导术和梯度下降法.mp4 | 2023-12-31 05:45:20 | 453.94 MB |
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17.17激活函数的选型.mp4 | 2023-12-31 05:45:20 | 408.82 MB |
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18.18权重初始化的方法.mp4 | 2023-12-31 05:45:20 | 401.31 MB |
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19.19.Softmax函数和负采样.mp4 | 2023-12-31 05:45:20 | 394.78 MB |
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20.20.温度Softmax和Softmax的数学推导.mp4 | 2023-12-31 05:45:20 | 417.25 MB |
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21.21.梯度下降法的改良.mp4 | 2023-12-31 05:45:20 | 450.64 MB |
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22.22.卷积神经网络CNN.mp4 | 2023-12-31 05:45:20 | 415.95 MB |
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23.23.深入理解卷积神经网络CNN.mp4 | 2023-12-31 05:45:20 | 410.72 MB |
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24.24.深入理解卷积神经网络CNN2.mp4 | 2023-12-31 05:45:20 | 516.74 MB |
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25.25.自然语言处理-语言模型.mp4 | 2023-12-31 05:45:20 | 464.79 MB |
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26.26.自然语言处理-word2vec.mp4 | 2023-12-31 05:45:20 | 346.57 MB |
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27.27自然语言处理-文本分类.mp4 | 2023-12-31 05:45:20 | 401.47 MB |
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28.28LSTM模型.mp4 | 2023-12-31 05:45:20 | 392.08 MB |
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29.29.Attention模型.mp4 | 2023-12-31 05:45:20 | 410.67 MB |
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30.30.Transformer和bert.mp4 | 2023-12-31 05:45:20 | 439.09 MB |
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31.31.Bert模型详解（更多课程微信：582229）.mp4 | 2023-12-31 05:45:20 | 123.15 MB |