mnielsen/neural-networks-and-deep-learning

This repository contains the Python code samples that accompany the book "Neural Networks and Deep Learning" by Michael Nielsen. The book is a free online resource that explains how neural networks, the foundational technology behind modern AI, actually work, starting from first principles. The code here is meant to be read alongside the book, giving you runnable examples that demonstrate the concepts explained in the text. The code is written in Python and is primarily intended as a companion to the written material rather than a standalone toolkit. The author has stated he does not intend to add new features or update the code for newer versions of Python, it was written for Python 2.6 or 2.7 and is kept as-is for historical consistency with the book. A community fork with Python 3 compatibility exists separately. You would use this repository if you are working through the "Neural Networks and Deep Learning" book and want to run the code examples yourself, or if you want to study a clear, educational implementation of neural network training written without heavy frameworks. The code is released under the MIT license, which means you are free to use, copy, and modify it for any purpose.