CS229 (Cs229)

1. Introduction to Linear Regression and Gradient Descent Purpose: Introduces linear regression as a foundational supervised learning algorithm. Content Highlights: Explanation of hypothesis formulation. Detailed notation and definitions (parameters, input vectors, target variables). Step-by-step derivation of cost function

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Supervised learning Linear Regression 1 LMS algorithm 2 The normal equations 2.1 Matrix derivatives 3 Probabilistic interpretation and more