# Introduction Linear and Quadratic Discriminant Analysis (LDA and QDA) are two classic classifiers used in machine learning. LDA uses a linear decision surface, while QDA uses a quadratic decision surface. These classifiers are popular because they have closed-form solutions, work well in practice, and have no hyperparameters to tune. In this lab, we will explore how to perform LDA and QDA using scikit-learn, a popular machine learning library in Python. ## 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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