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The following schedule is tentative and is being updated.
August
| Week | Topic | Lecture Notes | Reading | Assignments |
|---|---|---|---|---|
| Week 1: Aug 22, 24 | Course overview. Jupyter notebooks. Simple neural networks. | |||
| Week 2: Aug 29, 30 | Regression. Introduction to neural networks. Jupyter notebook animations. |
September
| Week | Topic | Lecture Notes | Reading | Assignments |
|---|---|---|---|---|
| Week 3: Sept 5, 7 | Python clases. Design of NeuralNetwork class. | |||
| Week 4: Sept 12, 14 | Optimizers. | |||
| Week 5: Sept 19, 21 | Introduction to classification. | |||
| Week 6: Sept 26, 28 | Classification. Convolutional neural networks. |
October
| Week | Topic | Lecture Notes | Reading | Assignments |
|---|---|---|---|---|
| Week 7: Oct 3, 5 | Introduction to Jax and Pytorch. | |||
| Week 8: Oct 10, 12 | More convolutional neural networks. | |||
| Week 9: Oct 17, 19 | Introduction to reinforcement leanring. Learning to play games. | |||
| Week 10: Oct 24, 26 | Reinforcement learning for control of dynamic systems. |
November
| Week | Topic | Lecture Notes | Reading | Assignments |
|---|---|---|---|---|
| Week 11: Oct 31 Nov 2 | Recurrent neural networks. | |||
| Week 12: Nov 7, 9 | Unsupervised learning. Dimensionality reduction. Autoencorders. | |||
| Week 13: Nov 14, 16 | Clustering. | |||
| Fall Break: Nov 20-24 | No classes | |||
| Week 14: Nov 28, 30 | Ensemble methods. Mixture-of-experts. Transformers. |
December
| Week | Topic | Lecture Notes | Reading | Assignments |
|---|---|---|---|---|
| Week 15: Dec 5, 7 | Other topics in current research. | AI Scientists’ Perspectives on AI | ||
| Dec 11-15 | Final Exam Week | No Exams in this course |
start.1689710985.txt.gz · Last modified: 2023/07/18 14:09 by 127.0.0.1