# Introduction The decision tree classifier is a popular machine learning algorithm used for classification and regression problems. It is a tree-based model that partitions the feature space into a set of non-overlapping regions and predicts the target value for each region. In this lab, we will learn how to analyse the decision tree structure to gain further insight into the relation between the features and the target to predict. ## 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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