metadata

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.

💡 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.

For more of my projects, visit my Portfolio Site.