Collection of deep learning implementations with side-by-side notes

In plain words

This is a collection of deep learning implementations organized with parallel explanatory notes. It provides side-by-side code and documentation to help users understand how neural networks work. The resource is designed for developers and students learning deep learning concepts. The implementations cover various architectures and techniques, making it useful for both beginners seeking to understand fundamentals and practitioners looking for reference implementations.

written from the facts on this page · September 2026

From the sources

This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations, and the website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better. We are actively maintaining this repo and adding new implementations. for updates. Solving games with incomplete information such as poker withfrom nn.labml.ai

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  Annotated neural network implementations2020 · ▲7

  Implementations of neural networks with side-by-side notes

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  Simple and comprehensive tutorials in Deep Learning using TensorFlow2018 · github.com · ▲157

  Simple and comprehensive tutorials in TensorFlow. Contribute to easy-tensorflow/easy-tensorflow development by creating an account on GitHub.

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  Comprehensive Tutorials in Deep Learning Using TensorFlow2018 · github.com · ▲327

  :satellite: Simple and ready-to-use tutorials for TensorFlow - GitHub - instillai/TensorFlow-Course: :satellite: Simple and ready-to-use tutorials for TensorFlow

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  Deep Learning in TensorFlow – The Roadmap for Study and Learning2019 · github.com · ▲146

  :satellite: Organized & Useful Resources about Deep Learning with TensorFlow - astorfi/TensorFlow-World-Resources

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  TensorFlow-Resources – Organized and Useful Resources about TensorFlow2018 · github.com · ▲152

  :satellite: Organized & Useful Resources about Deep Learning with TensorFlow - astorfi/TensorFlow-World-Resources

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