Stanford CS229 Machine Learning | Spring 2026 | Lecture 3: Weighted Least Squares
The lecture establishes Maximum Likelihood Estimation (MLE) as a foundational principle to generalize modeling from continuous regression to discrete classification. It derives Logistic Regression and compares optimization techniques like SGD vs. Newton's method.
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