Week | Topics | Chapter(s) |
---|---|---|
1 | Introduction, Syllabus, Machine Learning review | DLB 1-5 |
2 | Evaluation, Implementation, Neural Networks | DLB 6 |
3 | Optimization, Training, Regularization | DLB 7,8 |
4 | Convolutional Neural Networks | DLB 9 |
5 | Generative CNNs | DLB 20.6 |
6 | Review, Exam 1 | |
7 | Recurrent Neural Networks | DLB 10 |
8 | SPRING BREAK | |
9 | Improving RNNs | |
10 | Adversarial Examples | |
11 | Securing Deep Learning Models | |
12 | Generative Adversarial Networks | DLB 20.10.4 |
13 | Improving GANs | |
14 | Review, Exam 2 | |
15 | Advanced Topics, Thanksgiving | |
16 | Research Presentations |