[01]1_ Introduction and Historical Context.zh_en
[02]2_ Data-driven approach, kNN, Linear Classification 1.zh_en
[03]3_ Linear Classification 2, Optimization.zh_en
[04]4_ Backpropagation, Neural Networks 1.zh_en
[05]5_ Neural Networks Part 2.zh_en
[06]6_ Neural Networks Part 3 _ Intro to ConvNets.zh_en
[07]7_ Convolutional Neural Networks.zh_en
[08]8_ Localization and Detection.zh_en
[09]9_Visualization, Deep Dream, Neural Style, Adversarial Examples.zh_en
[10]10_ Recurrent Neural Networks, Image Captioning, LSTM.zh_en
[11]11_ ConvNets in practice.zh_en
[12]12_ Deep Learning libraries.zh_en
[13]14_ Videos and Unsupervised Learning.zh_en
[14]13_ Segmentation, soft attention, spatial transformers.zh_en
[15]15_ Invited Talk by Jeff Dean.zh_en