Fundamentals of Machine Learning - Support Vector Machine (SVM) - Labs

This video tutorial covers support vector machines (SVMs), explaining their use in classification and regression tasks. It begins with an introduction to SVMs, followed by setting up necessary libraries like NumPy, SciPy, and Matplotlib. The tutorial then demonstrates data generation and visualization using Scikit-learn's make_blobs function. It explains linear SVMs, focusing on maximizing margins, and shows how to implement SVMs using Scikit-learn's SVC function. Finally, it discusses non-linear SVMs and the kernel trick, using the RBF kernel to handle complex decision boundaries.

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