Neural Networks for Beginners | The Math & Geometry of Perceptrons

Welcome to this beginner-friendly deep dive into Neural Networks!
In this video, I’ll explain the mathematical foundation and geometric intuition behind the Perceptron, the simplest and most fundamental model in Artificial Intelligence and Machine Learning.

We’ll start from scratch — understanding the equations, weights, bias, and activation functions — and then visualize how these concepts form a decision boundary that separates data points in space.

By the end, you’ll not only know how a perceptron works mathematically, but also develop a visual and intuitive understanding of what happens inside a neural network neuron.

📘 Topics Covered

What is a Perceptron?

Perceptron mathematical model (weighted sum + bias)

Activation functions and decision boundaries

Linear separability and geometric interpretation

How Perceptrons form the basis of Neural Networks

🧩 Who this video is for

Beginners in AI / ML / Deep Learning

Students who love mathematics and geometry

Teachers or self-learners looking for clear conceptual explanations