HOML = Hands-On Machine Learning
DL = Deep Learning (these are generally optional readings, but fill in a lot of great detail)
| Class # | Date | Topic | Reading | Assignment | Due |
| 1 | Tue, Jan 18 | Class Introduction | Syllabus | ||
| 2 | Thu, Jan 20 | Multi-Layer Neural Networks Background: Python Basics | HOML CH 10 (pp. 279-295) Depth: DL CH 6-6.3 Background: Introduction to Python for Programmers (video on Canvas) | ||
| 3 | Tue, Jan 25 | Backpropagation | Depth: DL CH 6.4-6.5 | ||
| 4 | Thu, Jan 27 | Our Computational Environment | HOML CH 10 (pp. 295-314) | ||
| 5 | Tue, Feb 1 | Visualizing and Tuning Models | HOML CH 10 (rest) | ||
| 6 | Thu, Feb 3 | Training Deep Networks I | HOML CH 11 (pp. 331-351) Depth: DL CH 8-8.3) | HW 0 | |
| 7 | Tue, Feb 8 | Training Deep Networks II | HOML CH 11 (rest) Depth: DL CH 8.4-8.6 | ||
| 8 | Thu, Feb 10 | Data Handling in TensorFlow I | HOML CH 13 (pp. 413-430) | HW 1 | HW 0 |
| 9 | Tue, Feb 15 | Data Handling in TensorFlow II | HOML CH 13 (rest) | ||
| 10 | Thu, Feb 17 | Convolutional Neural Networks I | HOML CH 14 (pp. 445-453) Depth: DL 9-9.2, 9.10 | HW 2 | HW 1 |
| 11 | Tue, Feb 22 | Convolutional Neural Networks II | HOML CH 14 (pp. 453-460) Depth: DL 9.3-9.4 | ||
| 12 | Thu, Feb 24 | Convolutional Neural Networks III | HOML CH 14 (pp. 460-483) | HW 3 | HW 2 |
| 13 | Tue, Mar 1 | Convolutional Neural Networks IV | HOML CH 14 (rest) | ||
| 14 | Thu, Mar 3 | Convolutional Neural Networks V | n/a | HW 4 | HW 3 |
| 15 | Tue, Mar 8 | Recurrent Neural Networks | HOML CH 15 (pp. 497-511) Depth: DL 10-10.2 | ||
| 16 | Thu, Mar 10 | Recurrent Neural Networks: Memory | HOML CH 15 (pp. 511-518) Depth: DL 10.7- | ||
| - | Tue, Mar 15 | Spring Break | |||
| - | Thu, Mar 17 | Spring Break | |||
| 17 | Tue, Mar 22 | Recurrent Neural Networks: Memory | HOML CH 15 (pp. 518-523) | ||
| 18 | Thu, Mar 24 | Recurrent Neural Networks: Natural Language Processing | HOML CH 16 (pp. 525-542) Depth: DL 12.4-12.4.4 | ||
| 19 | Tue, Mar 29 | Recurrent Neural Networks: Machine Translation | HOML CH 16 (pp. 542-554) Depth: DL 12.4.5 | HW 5 | HW 4 |
| 20 | Thu, Mar 31 | Recurrent Neural Networks: Attention | HOML CH 16 (pp. 554-565) | ||
| 21 | Tue, Apr 5 | Transformer Networks I | TBD | HW 6 | HW 5 |
| 22 | Thu, Apr 7 | Transformer Networks II | TBD | ||
| 23 | Tue, Apr 12 | Autoencoders | HOML CH 17 (pp. 567-579) Depth: DL 14-14.5 | ||
| 24 | Thu, Apr 14 | Convolutional Autoencoders | HOML CH 17 (pp. 579-586) Depth: DL 14.6 | HW 7 | HW 6 |
| 25 | Tue, Apr 19 | Variational Autoencoders | HOML CH 17 (pp. 586-591) | ||
| 26 | Thu, Apr 21 | Generative Adversarial Networks | HOML CH 17 (pp. 591-598) | ||
| 27 | Tue, Apr 26 | Style Transfer and Cycle GANs | HOML CH 17 (rest) | HW 8 | HW 7 |
| 28 | Thu, Apr 28 | Explainable Deep Networks I | TBD | ||
| 29 | Tue, May 3 | Explainable Deep Networks I | TBD | ||
| 30 | Thu, May 5 | Looking Forward | n/a | HW 8 | |
| 29 | Tue, May 10 | No final exam | n/a |
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