EE 641: Deep Learning Systems

Aug 26

• lecture Lecture 01a: Introduction, PyTorch, and Deep Learning Review
• lecture Lecture 01b: Advanced CNN Architectures
• homework Homework 1 assigned

Sep 02

• lecture Lecture 02: Object Detection and Segmentation
• homework Homework 2 assigned

Sep 09

• lecture Lecture 03: Multi-Scale Detection and Spatial Regression

Sep 16

• lecture Lecture 03a: Generative Models: Energy-Based Models and Adversarial Training
• homework Homework 3 assigned

Sep 23

• lecture Lecture 03b: Generative Models: GAN Architectures, Evaluation, and VAEs

Sep 30

• lecture Lecture 04a: Recurrent Neural Networks
• homework Homework 4 assigned

Oct 07

• lecture Lecture 04b: Sequence-to-Sequence Models
• lecture Lecture 06: Transformers. Large Language Models (LLMs) and Mixture of Experts (MoE)

Oct 14

• lecture Lecture 05: Attention
• lecture Lecture 07a: Reinforcement Learning Principles
• homework Homework 5 assigned
• project Project Overview

Oct 21

• lecture Lecture 07b: Reinforcement Learning Applications

Oct 28

• exam Exam (HW + weeks 4–9)

Nov 02

• project Initial Proposal due

Nov 04

• project Project proposal meetings

Nov 06

• project Revised Proposal due

Nov 18

• project Project meetings

Dec 02

• project Presentation due
• project Project presentations (mandatory) — extended time

Dec 06

• project Final Report due
• project Model Card due
• project Video due
• project Source Code due