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https://github.com/markusschanta/awesome-keras

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

List: awesome-keras

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A curated list of awesome Keras projects, libraries and resources

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# Awesome Keras [![Awesome](https://awesome.re/badge.svg)](https://awesome.re) [![Hits](https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2Fmarkusschanta%2Fawesome-keras&count_bg=%2379C83D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=hits&edge_flat=false)](https://hits.seeyoufarm.com)



A curated list of awesome [Keras](http://keras.io/) projects, libraries and resources. Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation.





	


	Awesome Keras logo

	


	

🎉 This project is brand new: Your 🤝 **contributions** 🤝 and ⭐️ **stars** ⭐️ are much appreciated! 🎉




## Contents



- [Core Libraries](#core-libraries)

- [Frameworks](#frameworks)

- [Network Visualisation](#networkvisualization)

- [Examples/Notebooks](#examplesnotebooks)

- [Documentation](#documentation)

- [Community Resources](#community-resources)



---



## Core Libraries



- [keras](https://github.com/keras-team/keras) - Deep learning for humans.

- [autokeras](https://github.com/keras-team/autokeras) - AutoML library for deep learning.

- [keras-tuner](https://github.com/keras-team/keras-tuner) - Hyperparameter tuning for humans.

- [keras-cv](https://github.com/keras-team/keras-cv) - Industry-strength Computer Vision workflows with Keras.

- [keras-nlp](https://github.com/keras-team/keras-nlp) - Development environment with seamless data transmission from one language to another.



## Frameworks



- [byteps](https://github.com/bytedance/byteps) - A high performance and generic framework for distributed DNN training.

- [deep-learning-model-convertor](https://github.com/ysh329/deep-learning-model-convertor) - An overview of packages for model conversion between frameworks.

- [deepo](https://github.com/ufoym/deepo) - A collection of/framework to create deep learning Docker images.

- [einops](https://github.com/arogozhnikov/einops) - A library for flexible and powerful tensor operations to make code more readable and reliable.

- [horovod](https://github.com/horovod/horovod) - A distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

- [hyperas](https://github.com/maxpumperla/hyperas) - Keras + Hyperopt: A simple wrapper for hyperparameter optimization.

- [keras-rl](https://github.com/keras-rl/keras-rl) - Deep reinforcement learning for Keras.

- [MMdnn](https://github.com/microsoft/MMdnn) - A cross-framework tool to convert, visualize and diagnose deep learning models.

- [ncnn](https://github.com/Tencent/ncnn) - A high-performance neural network framework optimized for mobile platforms.

- [onnx](https://github.com/onnx/onnx) - An open standard for machine learning interoperability.

- [wandb](https://github.com/wandb/wandb) - A tool for visualizing and tracking your machine learning experiments.



## Network Visualisation



- [keras-sequential-ascii](https://github.com/stared/keras-sequential-ascii) - An ASCII summary for simple sequential models in Keras.

- [keras-vis](https://github.com/raghakot/keras-vis) - A neural network visualization toolkit for keras.

- [netron](https://github.com/lutzroeder/netron) - A visualizer for neural network, deep learning and machine learning models.

- [tensorspace](https://github.com/tensorspace-team/tensorspace) - A 3D visualization framework for neural networks.

- [TtDoVAoNN](https://github.com/ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network) - A list of tools to design or visualize architecture of neural networks.

- [visualkeras](https://github.com/paulgavrikov/visualkeras) - A Python package to help visualize Keras neural network architectures.



## Examples/Notebooks



- [ASRT_SpeechRecognition](https://github.com/nl8590687/ASRT_SpeechRecognition) - A deep learning-Based Chinese speech recognition system.

- [D2L.ai](https://github.com/d2l-ai/d2l-en) - An interactive deep learning book with multi-framework code, math, and discussions. 

- [data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks) - A collection of data science notebooks (dedicated [Keras section](https://github.com/donnemartin/data-science-ipython-notebooks#keras-tutorials)).  

- [deepjazz](https://github.com/jisungk/deepjazz) - Deep learning-driven jazz music generation using Keras and Theano.

- [donkeycar](https://github.com/autorope/donkeycar) - Open source hardware and software platform to build a small scale self driving car.

- [image-super-resolution](https://github.com/idealo/image-super-resolution) - A implementation to scale images using residual dense and adversarial networks.

- [imgclsmob](https://github.com/osmr/imgclsmob) - A sandbox for training convolutional neuronal networks.

- [keras-attention-mechanism](https://github.com/philipperemy/keras-attention-mechanism) - A many-to-one attention mechanism implementation in Keras.

- [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN) - A Keras implementation of Generative Adversarial Networks.

- [Mask_RCNN](https://github.com/matterport/Mask_RCNN) - An implementation of Mask R-CNN for object detection and segmentation on Keras and TensorFlow.

- [satellite-image-deep-learning](https://github.com/robmarkcole/satellite-image-deep-learning) - A collection of resources relating to deep learning with satellite & aerial imagery.

- [Screenshot-to-code](https://github.com/emilwallner/Screenshot-to-code) - A neural network that transforms a design mock-up into a static website.

- [sketch-code](https://github.com/ashnkumar/sketch-code) - A Keras model to generate HTML code from hand-drawn website mockups.

- [spektral](https://github.com/danielegrattarola/spektral) - Graph Neural Networks with Keras and Tensorflow.

- [textgenrnn](https://github.com/minimaxir/textgenrnn) - A library that allows simple training of text-generating neural networks with a few lines of code.

- [unet](https://github.com/zhixuhao/unet) - An implementation of U-Net using Keras.



## Documentation



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



## Community Resources



- GitHub - Search: [keras](https://github.com/search?type=Repositories&q=keras)

- GitHub - Topics: [keras](https://github.com/topics/keras), [tensorflow](https://github.com/topics/tensorflow), [neural-networks](https://github.com/topics/neural-networks)

- Gitter - [Keras Gitter Chatroom](https://gitter.im/Keras-io/Lobby)

- [kandi Kits Topic](https://kandi.openweaver.com/explore/keras) - Discover popular Keras libraries, top authors, trending project kits, discussions, tutorials & learning resources.

- Mailing Lists - [Keras users mailing list](https://groups.google.com/g/keras-users)

- PyPI - [``Keras``](https://pypi.org/project/keras/)

is the PyPI Keras project.

- Stack Overflow - Tags: [keras](https://stackoverflow.com/questions/tagged/keras?tab=Votes)