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• file:024.5-6 Dropout代码实现.mp4
• file:049.8-5 ResNet.mp4
• file:031.6-5 随机梯度下降法.mp4
• file:098.16-3 DALL-E模型.mp4
• file:002.1-2 初识深度学习.mp4
• file:077.12-5 Swin Transformer模型.mp4
• file:057.10-1 深度循环神经网络.mp4
• file:084.13-6 图像生成.mp4
• file:1_9-1-演员评论家算法核心思想和原理.mp4
• file:7_9-7-SAC代码实现.mp4
• file:2_10-2-Dyna-Q算法.mp4
• file:3_2-3-概率.mp4
• file:1_11-1模仿学习.mp4
• file:1_12-1-项目实战：Gym游戏.mp4
• file:09-6非线性SVM：核技巧.mp4
• file:06-10LASSO和岭回归代码实现.mp4
• file:15-5如何深入研究机器学习.mp4
• file:05-2线性回归核心思想和原理.mp4
• file:04-9KNN优缺点和适用条件.mp4
• file:04-6超参数.mp4
• file:03-4JupyterNotebook基础使用.mp4
• file:03-3Anaconda命令行操作.mp4
• file:07-7决策树回归任务代码实现.mp4