SVMs Explained: The Geometry of Intelligence

In this video, I've tried to explain the support vector machines, or SVMs, in an intuitive way using manim animations. First, I have explained the core ideas of support vector machines using animations, and then went into the mathematics of it, although I did not explain how to take derivatives and all, but rather did it directly, assuming the viewer can do it. And after explaining the mathematics of it, I have also explained what happens when the data is not linearly separable and how we use kernel functions (also known as the Kernel Trick), and then using a few famous kernels to simulate an SVM working.

chapters:-

0:00 Introduction to SVMs
02:12 Mathematics of SVMs
12:14 Problem of Linear separability
14:20 The Kernel Function
15:52 Kernel Trick Example
18:04 simulating SVMs using some kernels

---------------------------------------------------------------------------------------------------------------------------


📚 Welcome to the Channel!
If you're passionate about learning complex concepts in the simplest way possible, you're in the right place. I create visual explanations using animations to make topics more intuitive and engaging—especially in Algorithms, AI, machine learning, and beyond.

🎥 Animations created using Manim:
Manim is an open-source Python library for creating mathematical animations. Learn more or try it yourself:
🔗 https://www.manim.community

Let's Connect:-

GitHub:- https://github.com/ByteQuest0
Reddit:-   / ranjan4045