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• file:05-10复杂逻辑回归及代码实现.mp4
• file:06-2损失函数.mp4
• file:06-5过拟合与欠拟合.mp4
• file:09-4SVM软间隔.mp4
• file:14-5概率图模型优缺点和适用条件.mp4
• file:11-7结合策略：Stacking方法.mp4
• file:030.6-4 梯度下降.mp4
• file:024.5-6 Dropout代码实现.mp4
• file:077.12-5 Swin Transformer模型.mp4
• file:048.8-4 GoogLeNet.mp4
• file:042.7-4 卷积层常见操作.mp4
• file:089.14-5 项目实战：猫狗大战.mp4
• file:061.10-5 复杂循环神经网络代码实现.mp4
• file:026.5-8 模型文件的读写.mp4
• file:2_5-2-策略迭代.mp4
• file:5_3-5-深度学习库PyTorch的安装.mp4
• file:1_6-1-蒙特卡洛方法.mp4
• file:2_10-2-Dyna-Q算法.mp4
• file:4_10-4-基于模型的策略优化.mp4
• file:3_3-3-Jupyter-Notebook快速上手.mp4