Gaussian Process Regression and Classification

# Introduction

In this lab, we will explore Gaussian Processes (GP), a supervised learning method used for regression and probabilistic classification problems. Gaussian Processes are versatile and can interpolate observations, provide probabilistic predictions, and handle different types of kernels. In this lab, we will focus on Gaussian Process Regression (GPR) and Gaussian Process Classification (GPC) using the scikit-learn library.

## 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.