| Date | Content | Reading | Slides and Notes |
|---|---|---|---|
| Intro | |||
| 1/8 Th | Introduction, machine learning review |
chapter 1-4 of Dive into Deep Learning, Zhang et al
https://playground.tensorflow.org/ |
Lecture 1, Lecture 1 (annotated) |
| 1/15 Th | Fully-connected neural networks, optimization algorithms, optimization techniques | chapter 5, 6, 12 of Dive into Deep Learning, Zhang et al | Lecture 2 , Lecture 2 (annotated), scribed notes on Clarke differential, positive homogeneity and auto-balancing |
| 1/22 Th | Advanced optimizers, optimization techniques | Chapter 12 of Dive into Deep Learning, Zhang et al. , He et al. on Kaiming initialization, blog of escaping saddle points, blog on how to escape saddle points efficiently | Lecture 3 , Lecture 3 (annotated), scribed notes on Kaiming initialization |
| 1/29 Th | Introduction to convolutional neural networks, advanced convolutional neural networks, Recurrent neural networks, LSTM | Chapter 7,8, 9, 10 of Dive into Deep Learning, Zhang et al. | Lecture 4, Lecture 4 (annotated) |
| 2/5 Th | Attention mmechnism, deep learning theory (approximation) | Chapter 11 of Dive into Deep Learning, Zhang et al. Chapter 1,2 of Matus Telgarsky's notes | Lecture 5, |
| 2/12 Th | |||
| 2/19 Tu | |||
| 2/26 Th | |||
| 3/5 Th | |||
| 3/12 Th | Project Presentation (Zoom) |