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