📘 Grokking Deep Learning — Julia Port & Learning

This repository organizes materials from the original book "Grokking Deep Learning" (mostly notebooks) for learning purposes and aims to port parts of the examples to Julia.

Grokking Deep Learning — Official page

ℹ️ Note: This repository may include the following submodules or references:

• Book: The original repository containing the source (mostly Python) example notebooks.
• BookJuliaPort: Community/third-party examples ported to Julia.

🎯 Primary Goals

• Use the original book's example notebooks (originally in Python) as learning material.
• Port examples step-by-step to Julia for educational comparison and experiments.
• Document design and numerical differences encountered during porting.

⚙️ Quick Start (Recommended)

Prerequisites: Julia 1.8 or later, git, and optionally jupyter (or jupyterlab).

1. Activate the Julia environment at the repository root and install packages:

julia --project=. -e 'import Pkg; Pkg.activate("."); Pkg.instantiate()'

If the repository contains submodules (on first clone), initialize them first:

git submodule update --init --recursive

2. To open the notebooks in Jupyter (requires the IJulia kernel):

julia --project=. -e 'import Pkg; Pkg.add("IJulia"); using IJulia; installkernel("Grok")'
jupyter lab

Or to run Pluto notebooks (if you prefer Pluto):

julia --project=. -e 'import Pkg; Pkg.add("Pluto"); using Pluto; Pluto.run()'

🗂️ Repository Structure (Summary)

• Book/: Original (mostly Python) notebooks and data files used as source material — usually a submodule of the original repo.
• BookJuliaPort/: Community / third-party Julia ports of examples (submodule).
• src/Grok.jl: Supporting Julia code (utilities used during porting).
• Project.toml, Manifest.toml: Julia environment and dependencies.

Example data files: shakespear.txt, labels.txt, spam.txt, etc., are used by some notebooks.

🔧 Porting Guide (Short)

• Follow the original notebook cell-by-cell and reproduce the same numbers/outputs.
• Replace NumPy/Matplotlib calls with Julia equivalents such as LinearAlgebra, Plots.jl or Images.jl.
• For automatic differentiation examples, compare Zygote.jl with simple numeric-differentiation implementations.
• Record major numerical or performance differences as comments in the notebook when porting.

✅ Porting Checklist (example)

• Confirm whether original cell inputs/outputs are reproduced.
• Add required packages to Project.toml.
• Fix plot labels/axes so visualizations match the originals.

🤝 Contributing

• To port or modify, fork → branch → open a PR. Include: changed files, short run instructions, and (optionally) screenshots of reproduced examples.

📜 License & Copyright

• This repository is a learning-oriented port/notes collection. Respect the original author's copyright and licensing when using source materials — check the original work's license/permissions.

📬 Contact / Further Work

• Plans include porting more chapters to Julia or adding simple automated checks that validate cell reproduction.
• For questions or contributions, please use this repository's issue tracker.

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Refer to the Book/ directory 📂 for the list and links of original (Python) notebooks. Julia port examples will be added sequentially to src/.