fa25-cs540 cs540
Lecture 9: Linear Models & Linear Regression Lecture 9: Linear Models & Linear Regression
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Sign in to readLecture 9: Linear Models & Linear Regression
Introduction
Supervised Learning Review
Regression
Basic Recipe for Supervised Learning
Model Classes
The Problem with All Functions
Parametrized Model Classes
Training The Model
Gradient Descent
Gradients
Gradient Descent Algorithm
Train vs Test
Linear Regression
Notational Trick
Linear Regression Setup
Finding The Estimated Parameters
1. Gradient Descent
2. Closed-Form Solution (Normal Equations)
Evaluating The Model
Logistic Regression
Practice Problems
Key Takeaways
Suggested Reading