# Introduction Support Vector Machines (SVMs) are used for classification and regression analysis. SVMs find the best possible line or hyperplane that separates the data into different classes. The line or hyperplane that maximizes the distance between the two closest data points from different classes is called the margin. In this lab, we will explore how the parameter `C` affects the margin in a linear SVM. ## 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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