Neural Network base character recognition (OCR) from Scratch.

In this video, I walk you through the entire process of building an Optical Character Recognition (OCR) system from scratch—without relying on any libraries! We start with the foundational math behind neural networks, including forward propagation, backpropagation, and matrix calculations. I’ll also guide you through coding a simple drawing canvas to capture characters in real time, and implementing a live character detection system, all using raw code. Whether you're curious about the math behind neural networks or how to create your own OCR system step-by-step, this video covers it all.

Key topics covered:
Neural network fundamentals: forward pass, backpropagation, and matrix calculations
Coding a drawing canvas to capture live input
Character recognition using neural networks
Implementing OCR without external libraries
This is perfect for anyone interested in learning how OCR works under the hood, building machine learning models from scratch, or diving deep into the mathematics of neural networks.

If you're passionate about machine learning, computer vision, or just want to sharpen your coding skills, this video is for you!

Don’t forget to like, comment, and subscribe for more in-depth coding tutorials.