Machine Learning Cross-Validation with Python

# Introduction

In machine learning, cross-validation is a technique used to evaluate the performance of a model on an independent dataset. It helps to prevent overfitting by providing a better estimate of how well the model will generalize to new, unseen data.

In this lab, we will explore the concept of cross-validation and how to implement it using the scikit-learn library in Python.

## VM Tips

After the VM startup is done, click the top left corner to switch to the **Notebook** tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.