| Event Type | Date | Description | Course Material |
| Lecture | Aug 27 | Overview of Deep Learning Applications |
[slides]
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| Lecture | Sep 3 |
History of Deep Learning Assignment #0 available |
[slides] |
| Lecture | Sep 10 | Stochastic Gradient Descent, Neural Networks, & Backpropagation | [slides] |
| Lecture | Sep 17 |
Neural Networks & Backpropagation (cont.) Asssigment #0 due Sept 16 11:59pm
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[slides] |
| Lecture | Sep 24 |
Introduction to ConvNets Assignment #1 available |
[slides]
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| Lecture | Oct 1 | Species of ConvNets | [slides] |
| Lecture | Oct 8 | Introduction to Transformers | [slides] |
| Lecture | Oct 15 |
Understanding and Visualizing Convnets & Introduction to Recurrent Neural Networks Assignment #1 due Oct 14 11:59pm |
[slides] |
| Lecture | Oct 22 |
Recurrent Neural Networks Applications Assignment #2 available |
[slides] |
| Lecture | Oct 29 | Recurrent Neural Networks Applications (cont.) | [slides] |
| Lecture | Nov 5 |
Recurrent Neural Networks Applications (cont.) Assignment #2 due Nov 6 11:59pm |
[slides] |
| Lecture | Nov 12 |
Deep Reinforcement Learning Understanding Neural Nets as Splines |
[slides] [slides] |
| Lecture | Nov 19 |
Understanding Neural Nets as Splines (cont.) Deep Reinforcement Learning Final Project Proposal due Nov 18 11:59pm |
[slides] [slides] |
| Lecture | Nov 26 | Thanksgiving – No class | |
| Lecture | Dec 3 |
Guest Lecture: Alan Lockett (NLP Expert) NLP + Deep Learning, Large Language Models Poster Timeslot Form due Dec 2 11:59pm |
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| Final Project | Dec 10 Dec 16 |
Project Presentation Project Report due 23:59 |