Saturday Morning Videos: Convolutional Neural Networks for Visual Recognition (Spring 2017 Stanford CS 231n)

Justin mentioned this on his twitter feed

Lecture videos for Stanford CS 231n 2017 are now available! Taught by me, @syeung10, and @drfeifei: https://t.co/cxDWygELyQ

— Justin Johnson (@jcjohnss) 11 août 2017

Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition by Stanford University School of Engineering 57:57

Lecture 2 | Image Classification by Stanford University School of Engineering 59:32

Lecture 3 | Loss Functions and Optimization by Stanford University School of Engineering 1:14:40

Lecture 4 | Introduction to Neural Networks by Stanford University School of Engineering 1:13:59

Lecture 5 | Convolutional Neural Networks by Stanford University School of Engineering 1:08:56

Lecture 6 | Training Neural Networks I by Stanford University School of Engineering 1:20:20

Lecture 7 | Training Neural Networks II by Stanford University School of Engineering 1:15:30

Lecture 8 | Deep Learning Software by Stanford University School of Engineering 1:18:07

Lecture 9 | CNN Architectures by Stanford University School of Engineering 1:17:40

Lecture 10 | Recurrent Neural Networks by Stanford University School of Engineering 1:13:09

Lecture 11 | Detection and Segmentation by Stanford University School of Engineering 1:14:26

Lecture 12 | Visualizing and Understanding by Stanford University School of Engineering 1:15:48

Lecture 13 | Generative Models by Stanford University School of Engineering 1:17:41

Lecture 14 | Deep Reinforcement Learning by Stanford University School of Engineering 1:04:01

Lecture 15 | Efficient Methods and Hardware for Deep Learning by Stanford University School of Engineering 1:16:52

Lecture 16 | Adversarial Examples and Adversarial Training by Stanford University School of Engineering 1:21:46

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