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MXNet - A Deep Learning Framework
MXNet is an open-source deep learning framework that allows you to define, train, and deploy deep neural networks on a wide array of devices, from cloud infrastructure to mobile devices. It is highly scalable, allowing for fast model training, and supports a flexible programming model and multiple languages. MXNet allows you to mix symbolic and imperative programming flavors to maximize both efficiency and productivity.
deep-learning neural-networks artificial-intelligenceCNTK - Computational Network Toolkit (CNTK)
The Microsoft Cognitive Toolkit is a free, easy-to-use, open-source, commercial-grade toolkit that trains deep learning algorithms to learn like the human brain. It is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph.
deep-learning neural-networks artificial-intelligencekeras - Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
deep-learning tensorflow theano neural-networks machine-learning data-sciencepytorch-tutorial - PyTorch Tutorial for Deep Learning Researchers
This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less than 30 lines of code. Before starting this tutorial, it is recommended to finish Official Pytorch Tutorial.
deep-learning pytorch-tutorial neural-networks pytorch tutorial tensorboardStarGAN - Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
PyTorch implementation of StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation. StarGAN can flexibly translate an input image to any desired target domain using only a single generator and a discriminator.
stargan gan image-to-image-translation pytorch generative-adversarial-network image-manipulation computer-vision neural-networksDeepSpeech - A TensorFlow implementation of Baidu's DeepSpeech architecture
Project DeepSpeech is an open source Speech-To-Text engine. It uses a model trained by machine learning techniques, based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow project to make the implementation easier.
deep-learning machine-learning neural-networks tensorflow speech-recognition speech-to-textkeras-rl - Deep Reinforcement Learning for Keras.
keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seamlessly integrates with the deep learning library Keras. Just like Keras, it works with either Theano or TensorFlow, which means that you can train your algorithm efficiently either on CPU or GPU. Furthermore, keras-rl works with OpenAI Gym out of the box. This means that evaluating and playing around with different algorithms is easy. Of course you can extend keras-rl according to your own needs. You can use built-in Keras callbacks and metrics or define your own. Even more so, it is easy to implement your own environments and even algorithms by simply extending some simple abstract classes. In a nutshell: keras-rl makes it really easy to run state-of-the-art deep reinforcement learning algorithms, uses Keras and thus Theano or TensorFlow and was built with OpenAI Gym in mind.
keras tensorflow theano reinforcement-learning neural-networks machine-learningTensorFlow - Artificial Intelligence Library from Google
TensorFlow is a library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture lets you deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code.
artificial-intelligence neural-networks machine-learning deep-learning numerical-computationtensorpack - A Neural Net Training Interface on TensorFlow
Tensorpack is a training interface based on TensorFlow. It's Yet Another TF high-level API, with speed, readability and flexibility built together.
tensorflow imagenet deep-learning reinforcement-learning neural-networks machine-learningml-agents - Unity Machine Learning Agents
Unity Machine Learning Agents (ML-Agents) is an open-source Unity plugin that enables games and simulations to serve as environments for training intelligent agents. Agents can be trained using reinforcement learning, imitation learning, neuroevolution, or other machine learning methods through a simple-to-use Python API. We also provide implementations (based on TensorFlow) of state-of-the-art algorithms to enable game developers and hobbyists to easily train intelligent agents for 2D, 3D and VR/AR games. These trained agents can be used for multiple purposes, including controlling NPC behavior (in a variety of settings such as multi-agent and adversarial), automated testing of game builds and evaluating different game design decisions pre-release. ML-Agents is mutually beneficial for both game developers and AI researchers as it provides a central platform where advances in AI can be evaluated on Unity’s rich environments and then made accessible to the wider research and game developer communities. For more information, in addition to installation and usage instructions, see our documentation home. If you have used a version of ML-Agents prior to v0.3, we strongly recommend our guide on migrating to v0.3.
reinforcement-learning unity3d deep-learning unity deep-reinforcement-learning neural-networksfacenet - Face recognition using Tensorflow
This is a TensorFlow implementation of the face recognizer described in the paper "FaceNet: A Unified Embedding for Face Recognition and Clustering". The project also uses ideas from the paper "Deep Face Recognition" from the Visual Geometry Group at Oxford. The code is tested using Tensorflow r1.7 under Ubuntu 14.04 with Python 2.7 and Python 3.5. The test cases can be found here and the results can be found here.
face-recognition tensorflow facenet deep-learning computer-vision face-detection mtcnn neural-networksopenface - Face recognition with deep neural networks.
Free and open source face recognition with deep neural networks. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. Additional support was provided by the Intel Corporation, Google, Vodafone, NVIDIA, and the Conklin Kistler family fund. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and should not be attributed to their employers or funding sources.
deep-learning face-recognition facenet face-detection neural-networksBender - Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.
Bender is an abstraction layer over MetalPerformanceShaders useful for working with neural networks. Bender is an abstraction layer over MetalPerformanceShaders which is used to work with neural networks. It is of growing interest in the AI environment to execute neural networks on mobile devices even if the training process has been done previously. We want to make it easier for everyone to execute pretrained networks on iOS.
machine-learning neural-networks metal apple iphone ios convolutional-neural-networks deep-learning deep-neural-networks residual-networksAugmentor - Image augmentation library in Python for machine learning.
Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independent, which is more convenient, allows for finer grained control over augmentation, and implements the most real-world relevant augmentation techniques. It employs a stochastic approach using building blocks that allow for operations to be pieced together in a pipeline. Augmentor is written in Python. A Julia version of the package is also being developed as a sister project and is available here.
augmentation machine-learning deep-learning neural-networksbrain.js - 🤖 Neural networks in JavaScript
brain.js is a library of Neural Networks written in JavaScript. 💡 Note: This is a continuation of the harthur/brain repository (which is not maintained anymore). For more details, check out this issue.
neural-network brain recurrent-neural-networks easy-to-use api web nodejs browser convolutional-neural-networks node stream ai artificial-intelligence brainjs brain.js feed-forward classifier neural network neural-networks machine-learning synapse recurrent long-short-term-memory gated-recurrent-unit rnn lstm gruchainer - A flexible framework of neural networks for deep learning
Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference. For more details of Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter. The stable version of current Chainer is separated in here: v3.
deep-learning neural-networks machine-learning gpu cuda cudnn numpy cupy chainer neural-networkLasagne - Lightweight library to build and train neural networks in Theano
For more details and alternatives, please see the Installation instructions. For support, please refer to the lasagne-users mailing list.
deep-learning-library neural-networks theanoMLAlgorithms - Minimal and clean examples of machine learning algorithms implementations
A collection of minimal and clean implementations of machine learning algorithms. This project is targeting people who want to learn internals of ml algorithms or implement them from scratch. The code is much easier to follow than the optimized libraries and easier to play with. All algorithms are implemented in Python, using numpy, scipy and autograd.
machine-learning deep-learning neural-networks machine-learning-algorithmsMachine-Learning-Tutorials - machine learning and deep learning tutorials, articles and other resources
This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resources. Other awesome lists can be found in this list. If you want to contribute to this list, please read Contributing Guidelines.
deep-learning-tutorial machine-learning machinelearning deeplearning neural-network neural-networks deep-neural-networks awesome-list awesome list deep-learningdeep-reinforcement-learning - Repo for the Deep Reinforcement Learning Nanodegree program
This repository contains material related to Udacity's Deep Reinforcement Learning Nanodegree program. The tutorials lead you through implementing various algorithms in reinforcement learning. All of the code is in PyTorch (v0.4) and Python 3.
deep-reinforcement-learning reinforcement-learning reinforcement-learning-algorithms neural-networks pytorch pytorch-rl ddpg dqn ppo dynamic-programming cross-entropy hill-climbing ml-agents openai-gym-solutions openai-gym rl-algorithms
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