Generalized Linear Models and Linear Regression - Lecture 11
Overview
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Learn about key concepts in data science and statistical modeling through this comprehensive lecture covering generalized linear models, linear regression, and nonlinear basis functions. Explore practical examples using design matrices while understanding the importance of regularization and point estimation in preventing overfitting. Gain valuable insights into the mathematical foundations and practical applications of these statistical techniques used in modern data analysis and machine learning.
Syllabus
Intro
Overview
Outline
Generalized Linear Models
Linear Regression
Nonlinear Basis Function
Examples
Design Matrix
Overfeeding
Regularization
Point Estimation
Taught by
UofU Data Science