How to implement SVM (Support Vector Machine) from scratch with Python

In the 9th lesson of the Machine Learning from Scratch course, we will learn how to implement the SVM (Support Vector Machine) algorithm.

You can find the code here: https://github.com/AssemblyAI-Examples/Machine-Learning-From-Scratch

Previous lesson: https://youtu.be/aOEoxyA4uXU
Next lesson: https://youtu.be/6UF5Ysk_2gk

Welcome to the Machine Learning from Scratch course by AssemblyAI.
Thanks to libraries like Scikit-learn we can use most ML algorithms with a couple of lines of code. But knowing how these algorithms work inside is very important. Implementing them hands-on is a great way to achieve this.

And mostly, they are easier than you’d think to implement.

In this course, we will learn how to implement these 10 algorithms.
We will quickly go through how the algorithms work and then implement them in Python using the help of NumPy.

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