[Stanford CS229 04] Generative Leaning - GDA & Naive Bayes

OUTLINES Generative Learning Algorithms GDA Naive Bayes 1. Generative Learning Algorithms Generative Learning Algorithm model...

2023, Mar 07   —  5 minute read

[Stanford CS229 03] Generalized Linear Model (GLM) and Softmax Regression

OUTLINES Exponential Family Generalized Linear Models Softmax Regression (Multiclass Classification) 1. Exponential Family Distribution is...

2023, Mar 05   —  4 minute read

[Stanford CS229 02] Locally Weighted Regression and Logistic Regression

OUTLINES Locally Weighted Regression Probabilistic Interpretation (Maximum Log Likelihood) Logistic Regression Newton’s method 1. Locally...

2023, Feb 24   —  5 minute read

[Stanford CS229 01] Linear Regression and Gradient Descent

OUTLINES MULTIVARIATE LINEAR REGRESSION BATCH/ STOCHASTIC GRADIENT DESCENT NORMAL EQUATION 1. Multivariate Linear Regression 1.1....

2023, Feb 17   —  5 minute read