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Neural Network Layers · Awesome GitHub Repositories

3 repos

Awesome GitHub RepositoriesNeural Network Layers

Pre-defined architectural building blocks for constructing deep learning models, such as dense, convolutional, or recurrent layers.

Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Neural Network Layers. Refine with filters or upvote what's useful.

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  2. Artificial Intelligence & ML
  3. Machine Learning
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Awesome Neural Network Layers GitHub Repositories

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  • tensorflow/tensorflow

    tensorflow/tensorflow

    193,864GitHubView on GitHub↗

    TensorFlow is a comprehensive machine learning framework designed for the construction, training, and deployment of complex mathematical models. It utilizes a graph-based execution model that represents operations as directed acyclic graphs, enabling automatic differentiation and efficient parallel processing. The syst

    C++deep-learningdeep-neural-networksdistributed
  • pytorch/pytorch

    pytorch/pytorch

    97,601GitHubView on GitHub↗

    PyTorch is a machine learning framework centered on a GPU-ready tensor library that supports multi-dimensional array operations across both CPU and accelerator hardware. It provides a foundational infrastructure for mathematical computation and dynamic neural network construction, utilizing a tape-based automatic diffe

    Pythonautograddeep-learninggpu
  • d2l-ai/d2l-zh

    d2l-ai/d2l-zh

    75,708GitHubView on GitHub↗

    This project is an open-source, interactive educational platform designed to teach deep learning through a comprehensive, code-first curriculum. It provides a structured learning path that covers foundational mathematics, modern neural network architectures, and practical optimization techniques, enabling practitioners

    Pythonbookchinesecomputer-vision

Explore sub-tags

  • Convolution Layers1D, 2D, and 3D convolution and transposed convolution layers.
  • Normalization LayersLayers that normalize input activations to stabilize training and improve convergence.
  • Recurrent LayersModules for processing sequential data, including RNNs, LSTMs, and GRUs.