Schedule

This schedule is tentative and may change.

Date Topic Materials
June 5 Course Introcuction, Supervised Learning
June 10 Supervised Learning, Logistic Regression, HW1 Out
June 12 Review of Probability Theory, Linear Discriminant Analysis
June 17 Naive Bayes, Kernels, HW2 Out
June 19 Juneteenth Holiday
June 24 Support Vector Machine
June 26 Neural Networks
July 1 Backpropagation, Bias-Variance Tradeoff, HW3 Out
July 3 Decision Trees
July 8 Deep Learning
July 10 Convolutional Neural Networks
July 15 Boosting
July 17 PyTorch Tutorial, HW4 Out
July 22 Optimization for Deep learning
July 24 Markov Decision Processes
July 29 Reinforcement Learning
July 31 Unsupervised Learning
August 5 Attention Mechanism, Transformers
August 7 Project Presentations
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