Electrical and Computer Engineering 541: A Computational Introduction to Deep Learning
University of Southern California, Fall 2025
Schedule
Week 1
Aug 25: | Lecture 1 Deep Learning Principles and Paradigms | |
---|---|---|
Demo 1 Demos | ||
Homework 1 Homework 1 | ||
Reading 1 Reading 1 |
No Class -- No class, Labor Day
Week 2
Sep 8: | Lecture 2 Python Fundamentals | |
---|---|---|
Homework 2 Homework 2 | ||
Reading 2 Reading 2 |
Week 3
Sep 15: | Lecture 3 MMSE Estimation and Prediction | |
---|---|---|
Demo 3 Demos | ||
Homework 3 Homework 3 | ||
Reading 3 Reading 3 |
Week 4
Sep 22: | Lecture 4 Regression, Maximum Likelihood, and Information Theory | |
---|---|---|
Demo 4 Demos | ||
Reading 4 Reading 4 |
Week 5
Sep 29: | Lecture 5 Classification and Logistic Regression | |
---|---|---|
Homework 4 Homework 4 | ||
Reading 5 Reading 5 |
Week 6
Oct 6: | Lecture 6 Backpropagation | |
---|---|---|
Homework 5 Homework 5 | ||
Reading 6 Reading 6 |
Week 7
Oct 13: | Quiz 1 Weeks 1--6 | Sample -- Fall 2024 (Thursday, 09 October @ 12:00) |
---|---|---|
Homework 6 Homework 6 |
Week 8
Oct 20: | Lecture 7A Training Deep Neural Networks I | |
---|---|---|
Homework 7 Homework 7 | ||
Reading 7 Reading 7 |
Week 9
Oct 27: | Lecture 7B Training Deep Neural Networks II | |
---|---|---|
Homework 8 Homework 8 | ||
Reading 8 Reading 8 | ||
Project Proposal | Handouts and Templates |
Week 10
Nov 3: | Lecture 8 Convolutional Neural Networks (CNN) | |
---|---|---|
Homework 9 Homework 9 | ||
Reading 9 Reading 9 |
Week 11
Nov 10: | Lecture 8 Convolutional architectures. | |
---|---|---|
Demo 10 Demos | ||
Homework 9 Homework 9 | ||
Reading 10 Reading 10 |
Week 12
Nov 17: | Lecture 9 PyTorch: Optimizing training. Data engineering. | |
---|---|---|
Reading 11 Reading 11 |
Week 13
Nov 24: | Lecture 10 Auto-encoders and embedding. Recurrent neural networks (RNN). | |
---|---|---|
Reading 12 Reading 12 |
Week 14
Dec 1: | Quiz 2 Weeks 7--13 | Sample -- Fall 2024 (Friday, 28 November @ 12:00) |
---|
No matching items