[Stanford University School of Engineering] Convolutional Neural Networks for Visual Recognition (Spring 2017)

https://youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv 

Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)

 

 

 

Convolutional Neural Networks for Visual Recognition (Spring 2017)

 

 

Contents

Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition

Lecture 2 | Image Classification

Lecture 3 | Loss Functions and Optimization

Lecture 4 | Introduction to Neural Networks

Lecture 5 | Convolutional Neural Networks

Lecture 6 | Training Neural Networks I

Lecture 7 | Training Neural Networks II

Lecture 8 | Deep Learning Software

Lecture 9 | CNN Architectures

Lecture 10 | Recurrent Neural Networks

Lecture 11 | Detection and Segmentation

Lecture 12 | Visualizing and Understanding

Lecture 13 | Generative Models

Lecture 14 | Deep Reinforcement Learning

Lecture 15 | Efficient Methods and Hardware for Deep Learning

Lecture 16 | Adversarial Examples and Adversarial Training

 

 

 

ref.

http://cs231n.stanford.edu/

http://online.stanford.edu/