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--- |
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license: mit |
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datasets: [] |
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language: |
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- en |
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model_name: Micrograd AutoGrad Engine |
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library_name: pytorch |
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tags: |
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- micrograd |
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- autograd |
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- backpropagation |
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- neural-networks |
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- andrej-karpathy |
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--- |
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# Micrograd AutoGrad Engine: Backpropagation Implementation |
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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. |
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## Overview |
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- **Manual Backpropagation**: Building intuition and understanding of the gradient calculation process. |
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- **Implementation Notebooks**: Step-by-step code for implementing and understanding backpropagation and related concepts. |
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## Documentation |
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For a better reading experience and detailed notes, visit my **[Road to GPT Documentation Site](https://muzzammilshah.github.io/Road-to-GPT/Micrograd/)**. |
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> **💡 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. |
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## Acknowledgments |
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Notes and implementations inspired by the **Micrograd** video by [Andrej Karpathy](https://karpathy.ai/). |
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For more of my projects, visit my [Portfolio Site](https://muhammedshah.com). |
