# Introduction In this tutorial, we will learn about isotonic regression, which is a non-parametric regression technique that finds a non-decreasing approximation of a function while minimizing the mean squared error on the training data. We will use scikit-learn, a popular machine learning library in Python, to implement isotonic regression and compare it with linear regression. ## 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.
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