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awesome-keras

A curated list of awesome Keras projects, libraries and resources
https://github.com/markusschanta/awesome-keras

Last synced: 3 days ago
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  • Community Resources

  • Examples/Notebooks

    • ASRT_SpeechRecognition - A deep learning-Based Chinese speech recognition system.
    • D2L.ai - An interactive deep learning book with multi-framework code, math, and discussions. <!--lint disable double-link-->
    • data-science-ipython-notebooks - A collection of data science notebooks (dedicated [Keras section](https://github.com/donnemartin/data-science-ipython-notebooks#keras-tutorials)). <!--lint enable double-link-->
    • deepjazz - Deep learning-driven jazz music generation using Keras and Theano.
    • donkeycar - Open source hardware and software platform to build a small scale self driving car.
    • image-super-resolution - A implementation to scale images using residual dense and adversarial networks.
    • imgclsmob - A sandbox for training convolutional neuronal networks.
    • keras-attention-mechanism - A many-to-one attention mechanism implementation in Keras.
    • Keras-GAN - A Keras implementation of Generative Adversarial Networks.
    • Mask_RCNN - An implementation of Mask R-CNN for object detection and segmentation on Keras and TensorFlow.
    • Screenshot-to-code - A neural network that transforms a design mock-up into a static website.
    • sketch-code - A Keras model to generate HTML code from hand-drawn website mockups.
    • spektral - Graph Neural Networks with Keras and Tensorflow.
    • textgenrnn - A library that allows simple training of text-generating neural networks with a few lines of code.
    • unet - An implementation of U-Net using Keras.
  • Core Libraries

    • keras - Deep learning for humans.
    • autokeras - AutoML library for deep learning.
    • keras-tuner - Hyperparameter tuning for humans.
    • keras-cv - Industry-strength Computer Vision workflows with Keras.
    • keras-nlp - Development environment with seamless data transmission from one language to another.
  • Frameworks

    • byteps - A high performance and generic framework for distributed DNN training.
    • deep-learning-model-convertor - An overview of packages for model conversion between frameworks.
    • deepo - A collection of/framework to create deep learning Docker images.
    • einops - A library for flexible and powerful tensor operations to make code more readable and reliable.
    • horovod - A distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
    • hyperas - Keras + Hyperopt: A simple wrapper for hyperparameter optimization.
    • keras-rl - Deep reinforcement learning for Keras.
    • MMdnn - A cross-framework tool to convert, visualize and diagnose deep learning models.
    • ncnn - A high-performance neural network framework optimized for mobile platforms.
    • onnx - An open standard for machine learning interoperability.
    • wandb - A tool for visualizing and tracking your machine learning experiments.
  • Network Visualisation

    • keras-sequential-ascii - An ASCII summary for simple sequential models in Keras.
    • keras-vis - A neural network visualization toolkit for keras.
    • netron - A visualizer for neural network, deep learning and machine learning models.
    • tensorspace - A 3D visualization framework for neural networks.
    • TtDoVAoNN - A list of tools to design or visualize architecture of neural networks.
    • visualkeras - A Python package to help visualize Keras neural network architectures.
  • Documentation

    • cheatsheets-ai - A collection of deep learning/ML cheat sheets for ([Keras cheatsheet](https://github.com/kailashahirwar/cheatsheets-ai/blob/master/Keras.jpg)).