Grokking AI Algorithms

Get Grokking Artificial Intelligence Algorithms at Manning Publications

Requirements

• Python 3.9 or later (3.11 recommended)
• pip 23.1+ (comes with recent Python installers)
• Optional: PyTorch-compatible GPU for the heavy demos in Chapters 11–12

Setup

1. Install Python – download the latest 3.x release from python.org or use your platform package manager. Ensure python and pip point to the same interpreter (python -m pip --version).
2. Create a virtual environment (recommended so project dependencies stay isolated):
   • macOS / Linux:

     python3 -m venv .venv
     source .venv/bin/activate

   • Windows (PowerShell):

     py -3 -m venv .venv
     .\.venv\Scripts\Activate.ps1

3. Install dependencies:

   pip install --upgrade pip
   pip install -r requirements.txt

   PyTorch wheels are large; on Apple Silicon use the arm64 build from pip or follow the official instructions if you need CUDA support.
4. Run an example by moving into the chapter directory and executing the script:

   cd ch03-intelligent_search/informed_search
   python3 maze_astar.py

Overview

This is the official supporting code for the book, Grokking AI Algorithms, published by Manning Publications, authored by Rishal Hurbans.

The example implementations provided will make more sense if you've read the book, however, it might be somewhat useful to you otherwise.

The purpose of this repository is to act as a practical reference for examples of how the algorithms mentioned in the book can be implemented. This repository should not be consulted as the book is read page-by-page, but rather, when you're attempting to implement an algorithm or gain a more technical understanding from a programming perspective.

Rather Learn by exploring the code notebook in your browser? Click here: