Linear Models in Scikit-Learn

# Introduction

In this lab, we will explore linear models in scikit-learn. Linear models are a set of methods used for regression and classification tasks. They assume that the target variable is a linear combination of the features. These models are widely used in machine learning due to their simplicity and interpretability.

We will cover the following topics:

- Ordinary Least Squares
- Ridge Regression
- Lasso
- Logistic Regression
- Stochastic Gradient Descent
- Perceptron

## 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.