Assignments are due at 5 pm on designated days.
References are to:
- BB: Deep Learning Foundations and Concepts by Christopher M. Bishop with Hugh B [BB online access link].
- JM: Speech and Language Processing (3rd edition) by Dan Jurafsky and James H. M [JM online access link]
- SB: Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto [SB online access link].
| Week | Date | Recommended Reading | ||
| 1 | M 8/25 | L01: What is Machine Learning? Linear Models | BB 1 | |
| W 8/27 | L02: Maximum Likelihood Estimation, Validation and Regularization | BB 4.1 | ||
| F 8/29 | Recommended: Complete Setup and Background | |||
| 2 | M 9/1 | LABOR DAY | ||
| W 9/3 | L03: Logistic Regression and Classification, Cross Entropy and Evaluation Metrics | BB 5-5.1.4, 5.2.5-5.2.6, and 5.4-5.4.4 | ||
| F 9/5 | HW 1 Due | |||
| 3 | M 9/8 | L04: Artificial Neural Networks and the Multilayer Perceptron | BB 6.2-6.3.4, 6.3.6-6.4 | |
| W 9/10 | L05: Backpropagation and Minibatch Stochastic Gradient Descent | BB 7.2-7.4, 8.1-8.1.3, 9.3, 9.6.1 | ||
| F 9/12 | HW 2 Due | |||
| 4 | M 9/15 | L06: Convolutional Neural Networks and Image Recognition | BB 9.5, 10-10.2 | |
| W 9/17 | L07: Convolutional Neural Networks and Object Detection | BB 10.3-10.5 | ||
| F 9/19 | HW 3 Due | |||
| 5 | M 9/22 | L08: Sequence Models and the Transformer Architecture | BB 12-12.1, JM 8.1-8.7 | |
| W 9/24 | L09: Transformer Language Models and Autoregressive Generation | BB 12.2-12.2.4, JM 7 | ||
| F 9/26 | HW 4 Due | |||
| 6 | M 9/29 | L10: Fine-tuning, Low Rank Adaptation, KV-Caching, and Quantization | BB 12.3.5, JM 8.8 & 9 | |
| W 10/1 | L11: Chain of Thought, In-Context Learning, and Retrieval-Augmented Generation | JM 7.3 & 11 | ||
| F 10/3 | HW 5 Due | |||
| 7 | M 10/6 | L12: Vision Transformers and Contrastive Learning | BB 6.3.5, 12.4
(optional) Dosovitskiy et al. 2021 and Radford et al. 2021 |
|
| W 10/8 | Exam 1 (L01-09; HW 1-5) | |||
| F 10/10 | ||||
| 8 | M 10/13 | FALL BREAK | ||
| W 10/15 | L13: Generative Models and Diffusion | BB 20 | ||
| F 10/17 | ||||
| 9 | M 10/20 | L14: Text-to-Image and Guided Diffusion | BB 12.4 | |
| W 10/22 | L15: Markov Decision Processes | SB 3 | ||
| F 10/24 | HW 6 Due | |||
| 10 | M 10/27 | L16: Value-Based Reinforcement Learning | SB 4.4, 5.2-5.3, 6.5 | |
| W 10/29 | Finishing L16, Discussing Final Projects | |||
| F 10/31 | HW 7 Due | |||
| 11 | M 11/3 | L17: Policy-Based Reinforcement Learning | SB 13 | |
| W 11/5 | L18: State of the Art Models and Applications | |||
| F 11/7 | HW 8 Due | |||
| 12 | M 11/10 | Project Workshop | ||
| W 11/12 | Exam 2
(Emphasis on L08 – L17; HW 5 – HW 8) |
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| F 11/14 | ||||
| 13 | M 11/17 | Project Workshop | ||
| W 11/19 | Project Workshop | |||
| F 11/21 | ||||
| 14 | M 11/24 | Project Workshop | ||
| W 11/26 | THANKSGIVING BREAK | |||
| F 11/28 | THANKSGIVING BREAK | |||
| 15 | M 12/1 | Project Workshop | ||
| W 12/3 | Project Workshop | |||
| F 12/5 | Final Project Submission Deadline extended to 5 pm on Tuesday 12/9 |
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