HOML = Hands-On Machine Learning
| Class # | Date | Topic | Reading | Assignment | Due |
| 1 | Tue, Jan 17 | Class Introduction | Syllabus | HW -1 | |
| 2 | Thu, Jan 19 | Multi-Layer Neural Networks Background: Python Basics | HOML CH 10 (pp. 279-295) Background: Introduction to Python for Programmers | HW -1 | |
| 3 | Tue, Jan 24 | Backpropagation | n/a | ||
| 4 | Thu, Jan 26 | Our Computational Environment | HOML CH 10 (pp. 295-314) | ||
| 5 | Tue, Jan 31 | Training Deep Networks I | HOML CH 11 (pp. 331-351) | ||
| 6 | Thu, Feb 2 | Training Deep Networks II | HOML CH 11 (pp. 351-) | HW 0 | |
| 7 | Tue, Feb 7 | Training Deep Networks III | HOML CH 10 (pp. 314-) | ||
| 8 | Thu, Feb 9 | Convolutional Neural Networks I | HOML CH 14 (pp. 445-453) | HW 1 | HW 0 |
| 9 | Tue, Feb 14 | Convolutional Neural Networks II | HOML CH 14 (pp. 453-460) | ||
| 10 | Thu, Feb 16 | Convolutional Neural Networks III | HOML CH 14 (pp. 460-483) | HW 2 | HW 1 |
| 11 | Tue, Feb 21 | Convolutional Neural Networks IV | HOML CH 14 (pp. 483-) | ||
| 12 | Thu, Feb 23 | Data Handling in TensorFlow I | HOML CH 13 (pp. 413-424) | HW 3 | HW 2 |
| 13 | Tue, Feb 28 | Recurrent Neural Networks | HOML CH 15 (pp. 497-511) | ||
| 14 | Thu, Mar 2 | Recurrent Neural Networks: Memory | HOML CH 15 (pp. 511-518) | HW 4 | HW 3 |
| 15 | Tue, Mar 7 | Recurrent Neural Networks: Memory | HOML CH 15 (pp. 518-523) | ||
| 16 | Thu, Mar 9 | Recurrent Neural Networks: Natural Language Processing | HOML CH 13 (pp. 430-439); CH 16 (pp. 525-534) | ||
| - | Tue, Mar 14 | Spring Break | |||
| - | Thu, Mar 16 | Spring Break | |||
| 17 | Tue, Mar 21 | Recurrent Neural Networks: Sentiment Analysis | HOML CH 16 (pp. 534-542) | ||
| 18 | Thu, Mar 23 | Recurrent Neural Networks: Machine Translation | HOML CH 16 (pp. 542-548) | HW 5 | HW 4 |
| 19 | Tue, Mar 28 | Recurrent Neural Networks: Attention | HOML CH 16 (pp. 548-554) | ||
| 20 | Thu, Mar 30 | Transformer Networks I | HOML CH 16 (pp. 554-565) Attention is All You Need Transformer: Self-Attention [Part 1] | ||
| 21 | Tue, Apr 4 | Transformer Networks II | The Illustrated Transformer | HW 6 | HW 5 |
| 22 | Thu, Apr 6 | Autoencoders and U-Nets | HOML CH 17 (pp. 567-579) | ||
| 23 | Tue, Apr 11 | Convolutional Autoencoders | HOML CH 17 (pp. 579-586) | ||
| 24 | Thu, Apr 13 | Variational Autoencoders | HOML CH 17 (pp. 586-591) | HW 7 | HW 6 |
| 25 | Tue, Apr 18 | Autoencoders for Discovery of Dynamics | Data-Driven Discovery of Coordinates and Governing Equations | ||
| 26 | Thu, Apr 20 | Generative Adversarial Networks | HOML CH 17 (pp. 591-598) | ||
| 27 | Tue, Apr 25 | Diffusion-Based Generative Models | High-Resolution Image Synthesis with Latent Diffusion Models SDEDIT: Guided Image Synthesis and Editing with Stochastic Differential Equations | HW 8 | HW 7 |
| 28 | Thu, Apr 27 | Explainable Deep Networks I | TBD | ||
| 29 | Tue, May 2 | Explainable Deep Networks II | TBD | ||
| 30 | Thu, May 4 | Looking Forward | n/a | HW 8 | |
| 29 | Tue, May 9 | No final exam | n/a |
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