Intro to Regularization with Python

Improve machine learning performance with regularization.
Machine learning models need to perform well not only on their training data, but also on new data. In this course, you will learn how to use regularization to improve performance on new data. You will learn the most common techniques for regularization, how they work, and how to apply them.


* Minimize overfitting

* Apply ridge and lasso regularization

* Understand the bias-variance tradeoff


### Notes on Prerequisites
If you are a beginner, learn to build Machine Learning models from scratch in our [Machine Learning Fundamentals](https://www.codecademy.com/learn/paths/machine-learning-fundamentals) Skill Path.

• Intro to Regularization: Learn about regularization and how to implement it in Python.
• Lesson: An Introduction to Regularization in Machine Learning
• Quiz: Regularization
• Article: Implementing Regularization Methods in Python
• Project: Predict Wine Quality with Regularization
• Informational: Next Steps