CE/CZ 7454 Deep Learning for Data Science (Semester 1, AY2021-22)
This is a graduate-level course that serves as an (advanced) introduction to deep learning. In Semester 1 (Fall) 2021, I co-taught this course with Prof. Liu Ziwei. My part covers the following topics in 7 weeks:
  1. Introductory Linear Algebra
  2. Introductory Probability Theory
  3. Basic Machine Learning Models (Linear Regression, Logistic Regression, Multi-layer Perceptron)
  4. Convolutional Neural Network and Major Variants (ResNet, DenseNet, MobileNet, EfficientNet, Grouped Convolution, 3D Convolution, Temporal Convolution, etc.)
  5. Optimization of Neural Networks. [Slides]
  6. Regularization of Neural Networks.
AI 6103 Deep Learning (Semesters 1-2, AY2021-22)
This is a 13-week course for the Master of Science in Artificial Intelligence (MSAI) program. It covers most topics of CZ/CE 7454. Additionally, it covers structured predictions in both computer vision and natural language, as well as programming in PyTorch.