README.md

---
license: mit
datasets: []
language:
- en
model_name: Micrograd AutoGrad Engine
library_name: pytorch
tags:
- micrograd
- autograd
- backpropagation
- neural-networks
- andrej-karpathy
---

# Micrograd AutoGrad Engine: Backpropagation Implementation

This repository contains the implementation of **Backpropagation** using an **AutoGrad Engine**, inspired by the **Micrograd** video by Andrej Karpathy. It explores the foundations of training neural networks and implementing key operations from scratch.

## Overview
- **Manual Backpropagation**: Building intuition and understanding of the gradient calculation process.
- **Implementation Notebooks**: Step-by-step code for implementing and understanding backpropagation and related concepts.

## Documentation
For a better reading experience and detailed notes, visit my **[Road to GPT Documentation Site](https://muzzammilshah.github.io/Road-to-GPT/Micrograd/)**.

> **💡 Pro Tip**: This site provides an interactive and visually rich explanation of the notes and code. It is highly recommended you view this project from there.

## Acknowledgments
Notes and implementations inspired by the **Micrograd** video by [Andrej Karpathy](https://karpathy.ai/).

For more of my projects, visit my [Portfolio Site](https://muhammedshah.com).