Skip to main content

Tutorial 6 Model Selection: Cross-validation

Difficulty level
Beginner
Speaker
Duration
5:28

This is Tutorial 6 of a series on fitting models to data. We start with simple linear regression, using least squares optimization (Tutorial 1) and Maximum Likelihood Estimation (Tutorial 2). We will use bootstrapping to build confidence intervals around the inferred linear model parameters (Tutorial 3). We'll finish our exploration of regression models by generalizing to multiple linear regression and polynomial regression (Tutorial 4). We end by learning how to choose between these various models. We discuss the bias-variance trade-off (Tutorial 5) and Cross Validation for model selection (Tutorial 6).

Topics covered in this lesson
  • Implement cross-validation and use it to compare polynomial regression model
Prerequisites

Experience with Python Programming Language