MichalDanielDobrzanski/DeepLearningPython resource

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2830 stars · 1274 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Python 3.5.2 port of the companion scripts for the book 'Neural Networks and Deep Learning' (neuralnetworksanddeeplearning.com), including network.py, network2.py, and network3.py with Theano and CUDA support. It serves as runnable educational code for training and evaluating the neural networks described in the book's chapters.

Use cases

• learn how neural networks are implemented from scratch
• run the code examples from the neural networks and deep learning book
• train a simple MNIST classifier in Python
• study backpropagation and gradient descent implementations
• experiment with Theano-based convolutional networks with CUDA

When to choose

• you are reading the book and want working Python 3 code for its examples
• you want minimal, readable educational neural network implementations
• you want to see how Theano-era deep learning code was structured

When to avoid

• you need a modern deep learning framework like PyTorch or TensorFlow
• you want production-ready or actively maintained training code
• you cannot run Python 3.5-era dependencies such as Theano

Facets

learning-resource · maturity maintenance

deep-learning machine-learning gpu-computing deep-learning machine-learning education tutorials python cross-platform neural-networks theano book-companion-code cuda python3 gpu

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