Fundamentals of Deep Learning (Forked & Updated)

This repository is a fork of the official code companion to Fundamentals of Deep Learning, Second Edition, originally maintained by Nithin Buduma, Nikhil Buduma, Joe Papa, and other contributors.
All algorithms are implemented in PyTorch.

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✨ What’s different in this fork?

• PyTorch & Python updates
  Code patched to run on the latest stable Python (3.12) and PyTorch (2.3+) environments.
• Minimal fixes only
  Preserved the algorithms as-is; applied only compatibility fixes (e.g., deprecated APIs, dataset loading, tokenizer changes).
• Scope of changes
  Updates for Chapter 9 are complete; other chapters are under review.
• Colab-ready
  Verified notebooks run smoothly on Google Colab with only PyTorch/Datasets installation required.

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Guide to the repository

The structure follows the original:

• Each chapter’s examples are in the corresponding folder (e.g., Ch09_04_Dissecting_NTN.ipynb).
• Most examples are provided as Google Colab notebooks; some .py scripts are also included.
• Code from the First Edition remains in first_edition_archive/.

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Running the notebooks

You can run the Google Colab notebooks directly from this fork.
👉 Using Google Colab with GitHub

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Credits

Original authors:

• Nithin Buduma
• Nikhil Buduma
• Joe Papa

Additional contributors:

• Nicholas Locascio
• Mostafa Samir
• Surya Bhupatiraju
• Anish Athalye

Fork & updates for compatibility: [Jaehun Choe / jaydenchoe]

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