ECE 228 (2024 Spring)


Prof. Yuanyuan Shi,

Office hours: Tuesday 1-2pm (Location: Franklin Antonio Hall Room #)

Co-Instructor: Dr. Yufan Zhang, 

Teaching Assistants

Yuexin Bian,  Office Hour: Monday 4-5 pm (Location: Franklin Antonio Hall 4002)

Tz-Ying Wu, Office Hour: Thursday 4-5 pm (Location: TBD)

Han Guo,, Office Hour: Wednesday 11am-12pm (Location: Jacobs Hall Room 5101B)

Course Time and Location

Tuesday/Thursday, 11-12:20 pm, Pepper Canyon Hall 109


Part 1: Machine Learning / Deep Learning Fundamentals

Week 1: Course Logistics; supervised learning setup; linear regression [Lecture 1] [Lecture 2]

Week 2: Linear models for classification; Feature selection: ridge regression, Lasso; Bias and Variance Tradeoffs [Lecture 3] [Lecture 4]

Week 3: Neural network basics; computational graph and backpropagation; optimization and regularization 

Week 4: Temporal data modeling: RNN / LSTM/GRU,  Guassian Process [Taught by Yufan]

Week 5: Spatial and temporal data modeling: Spatial and temporal data modeling: CNN; Attention & Transformer

Part 2: Specialized Topics: Machine Learning for Physical Applications

Week 6: Review of ODEs and PDEs; Physics-informed machine learning

Week 7: Neural ODEs; Neural operators

Week 8: Deep Learning and Optimization: OptNet; ML to solve Optimization [Taught by Yufan]

Week 9: Deep Learning and Control: Model-based RL and model predictive control

Week 10: Final project presentation (in-class presentation)

Recommended Reading:

Week 1-2: An Introduction to Statistical Learning (with Applications in Python): Chapters 1-5

Week 3-5: Deep Learning, Part II: Chapters 6-11

Week 6 - 10: Papers and Discussions

Lecture Notes

Lecture 1: Introduction & Course Logistics