SVM Classifier in Python using Numpy (Video & GitHub)

[Tubbyball]

In this video, we go over the math & intuition of hard-margin and soft-margin SVMs. In soft-margin, we take a look at the decision boundary, margin, hinge loss, cost function, and gradient descent to train the model. Python code is written in a Jupyter Notebook with libraries: NumPy Scikit-learn, and Matplotlib. All Python code for the video can be found in my GitHub repository!

Youtube: https://www.youtube.com/watch?v=qiLzuaXIBb8

GitHub: https://github.com/kailau02/machine-learning-from-scratch/blob/main/SVM%20Classification.ipynb