Instructor(s)
Prof. Yuanyuan Shi, yyshi@ucsd.edu
Office hours: Tuesday 1-2pm (Location: Franklin Antonio Hall Room #)
Co-Instructor: Dr. Yufan Zhang, yuz254@ucsd.edu
Teaching Assistants
Yuexin Bian, yubian@ucsd.edu Office Hour: Monday 4-5 pm (Location: Franklin Antonio Hall 4002)
Tz-Ying Wu, tzw001@ucsd.edu Office Hour: Thursday 4-5 pm (Location: TBD)
Han Guo, h5guo@ucsd.edu, 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