Module 4: Bias-Variance Tradeoff

Module Overview

In this module, you will learn about the bias-variance tradeoff, a fundamental concept in machine learning that helps us understand model performance and generalization. You'll explore how to balance model complexity to avoid both underfitting and overfitting, and you'll learn about metrics for evaluating model performance.

Learning Objectives

• Understand and Define Bias
• Understand and Define Variance
• Describe the Bias / Variance Tradeoff
• Define Different Types of Biases

Guided Project

Open bias_variance_prop_lesson_DS39.ipynb in the GitHub repository below to follow along with the guided project:

Guided Project Video

Module Assignment

Complete the Module 4 assignment to practice bias-variance tradeoff techniques you've learned.

Assignment Solution Video

Resources

Documentation and Tutorials

• Scikit-learn: Metrics and Scoring
• Scikit-learn: Cross-validation
• Scikit-learn: Ridge Regression

Articles and Readings

• Understanding the Bias-Variance Tradeoff
• A Gentle Introduction to the Bias-Variance Trade-Off