- CS229 Machine Learning - Introduction and Overview
Stanford CS229 Machine Learning course notes covering supervised learning, unsupervised learning, and reinforcement learning.
3 min read en - CS229 Machine Learning - Linear Regression
Introduction to linear regression: variable definitions, probabilistic interpretation, LMS algorithm (gradient descent), and locally weighted regression.
4 min read en - CS229 Machine Learning - Logistic Regression
From regression to classification: logistic regression model, sigmoid function, and multi-class classification.
1 min read en - CS229 Machine Learning - Generalized Linear Models
Introduction to exponential family distributions and generalized linear models, unifying linear regression and logistic regression.
1 min read en