| Date | Event | Description | Materials | Announcements* |
|---|---|---|---|---|
| Monday, Jan 16 | NO CLASS (Martin Luther King Day) | |||
| Wednesday, Jan 18 | Lecture 1 | Introduction to Machine Learning, Regression | Readings: Bishop (Chapter 1, Chapter 3: 3.1-3.2), Deep Learning Book (Chapter 4, Chapter 5) Lecture: slides, recording |
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| Friday, Jan 20 | Recitation 1 | TBD | ||
| Monday, Jan 23 | Lecture 2 | Continue Introduction to Machine Learning, Regression | Readings: Bishop (Chapter 1, Chapter 3: 3.1-3.2), Deep Learning Book (Chapter 4, Chapter 5) Lecture: slides, recording |
|
| Wednesday, Jan 25 | Lecture 3 | Neural Networks I | Readings: Bishop (Chapter 5: 5.1-5.4), Deep Learning Book (Chapter 6) Lecture: slides, recording |
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| Friday, Jan 27 | Recitation 2 | Probability Distributions | Recitation: slides, recording | |
| Monday, Jan 30 | Lecture 4 | Neural Networks II | Readings: Bishop (Chapter 5: 5.1-5.4), Deep Learning Book (Chapter 7) Lecture: slides, recording |
Course add deadline |
| Wednesday, Feb 1 | Lecture 5 | Convolutional Neural Networks I | Readings: Deep Learning Book (Chapter 9) Lecture: slides, recording |
HW1 out |
| Friday, Feb 3 | Recitation 3 | Homework 1 Recitation | Recitation: slides, recording | |
| Monday, Feb 6 | Lecture 6 | Convolutional Neural Networks II / Start Graphical Models | Readings: Deep Learning Book (Chapter 9) Lecture: slides, recording |
|
| Wednesday, Feb 8 | Lecture 7 | Graphical Models: Directed Graphs | Readings: Bishop (Chapter 8) Lecture: slides, recording |
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| Friday, Feb 10 | Recitation 4 | Pytorch and AWS | ||
| Monday, Feb 13 | Lecture 8 | Graphical Models, Undirected Graphs / RBMs | Readings: Bishop (Chapter 8) Lecture: slides, recording |
|
| Wednesday, Feb 15 | Lecture 9 | Restricted Boltzmann Machines (RBMs) | Readings: Deep Learning Book (Chapter 20.3) Lecture: slides, recording |
HW1 due; HW 2 out |
| Friday, Feb 17 | Lecture 10 | Deep Belief Networks | Readings: Deep Learning Book (Chapter 20.3) Lecture: slides, recording |
|
| Monday, Feb 20 | Recitation 5 | Homework 2 Recitation | ||
| Wednesday, Feb 22 | Lecture 11 | Autoencoders | Readings: Deep Learning Book (Chapter 14) Lecture: slides, recording |
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| Friday, Feb 24 | - | - | ||
| Monday, Feb 27 | Lecture 12 | Graph Neural Networks: Guest Lecture from Minji Yoon | Lecture: slides, recording | Semester course drop deadline |
| Wednesday, Mar 1 | Lecture 13 | Language Modeling | Readings: Deep Learning Book (Chapter 10 and Chapter 12: 12.4) Lecture: slides, recording |
HW2 due |
| Friday, Mar 3 | Recitation 6 | TBD | Midway report due | |
| Monday, Mar 6 | NO CLASS (Spring Break) | |||
| Wednesday, Mar 8 | NO CLASS (Spring Break) | |||
| Friday, Mar 10 | NO CLASS (Spring Break) | |||
| Monday, Mar 13 | Lecture 14 | Sequence Models (Part 1) and Mid-term Review | Readings: Deep Learning Book (Chapter 10) Lecture: slides (MCMC), slides (review), recording |
|
| Wednesday, Mar 15 | Lecture 15 | Sequence Models (Part 2), Transformers | Readings: Deep Learning Book (Chapter 10) Lecture: slides, recording |
|
| Friday, Mar 17 | Recitation 7 | Recitation time used for mid-term exam | Mid-term exam | |
| Monday, Mar 20 | Lecture 16 | Variational Inference | Readings: Deep Learning Book (Chapter 19) Lecture: slides, recording |
HW3P1 out |
| Wednesday, Mar 22 | Lecture 17 | Multi-Modal Learning: Guest Lecture from Paul Pu Liang | Readings: TBA Lecture: slides, recording |
|
| Friday, Mar 24 | Recitation 8 | Homework 3 Part 1 Recitation | ||
| Monday, Mar 27 | Lecture 18 | Variational Autoencoders | Readings: Deep Learning Book (Chapter 20) Lecture: slides, recording |
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| Wednesday, Mar 29 | Lecture 19 | Markov Chain Monte Carlo | Readings: TBD Lecture: slides, recording |
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| Friday, Mar 31 | Recitation 9 | TBD | ||
| Monday, Apr 3 | Lecture 20 | Generative Adversarial Networks / Normalizing Flows | Readings: Deep Learning Book (Chapter 20: 20.10) Lecture: slides, recording |
HW3P1 due; Pass/Fail grade option deadline |
| Wednesday, Apr 5 | Lecture 21 | Diffusion Models | Readings: TBD Lecture: slides, recording |
HW3P2 out |
| Friday, Apr 7 | Recitation 10 | Homework 3 Part 2 Recitation | Readings: TBD Lecture: slides, recording |
|
| Monday, Apr 10 | Lecture 22 | Representation Learning for Reading Comprehension | Readings: TBD Lecture: slides, recording |
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| Wednesday, Apr 12 | Lecture 23 | Embodied AI: Language and Perception | Readings: TBD Lecture: slides, recording |
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| Friday, Apr 14 | NO CLASS (Carnival April 13th-15th) | |||
| Monday, Apr 17 | Lecture 24 | Integrating Domain-Knowledge into Deep Learning | Readings: TBD Lecture: slides, recording |
|
| Wednesday, Apr 19 | Lecture 25 | Generative Models for Data Augmentation | Readings: TBD Lecture: slides, recording |
HW3P2 due |
| Friday, Apr 21 | Recitation 11 | TBD | ||
| Monday, Apr 24 | Lecture 26 | Capsules | Readings: TBD Lecture: slides, recording |
|
| Wednesday, Apr 26 | Lecture 27 | Introduction to Reinforcement Learning | Final report due | |
| Friday, Apr 28 | TBA | TBA |
* all announcement dates are tentative and subject to change