# Introduction In machine learning, feature discretization is a method of reducing the number of continuous variables in a dataset by creating bins or intervals to represent them. This method can be useful in cases where the number of continuous variables is large, and the algorithm needs to be simplified for easier analysis. In this lab, we will demonstrate feature discretization on synthetic classification datasets. ## 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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