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Date	Description
October 5	Welcome/Overview, MLE, Linear regression
October 12	Linear regression with basis functions, Overfitting; Quiz 1
October 19	Bias-variance, Ridge regression, Lasso; Quiz 2
October 26	Gradient descent, Convexity, Logistic regression; Quiz 3
November 2	Classification, Logistic regression, Softmax, SVMs, Nearest neighbors, Bootstrap; Quiz 4
November 9	Interpretability, Distribution shift, Fairness, PAC learning, VC dimension, Kernels; guest lecture: Zhiming Huang and Claire Zhang; Quiz 5
November 16	Neural networks, Trees; Quiz 6
November 23	Boosting and ensembling methods; PCA, SVD, and k-means; Quiz 7
November 30	CNNs, attention, transformers, and sequence models; Quiz 8
December 7	Domain-specific models, online learning; no quiz