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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-sciencegorgonia - Gorgonia is a library that helps facilitate machine learning in Go.
Gorgonia is a library that helps facilitate machine learning in Go. Write and evaluate mathematical equations involving multidimensional arrays easily. If this sounds like Theano or TensorFlow, it's because the idea is quite similar. Specifically, the library is pretty low-level, like Theano, but has higher goals like Tensorflow.The main reason to use Gorgonia is developer comfort. If you're using a Go stack extensively, now you have access to the ability to create production-ready machine learning systems in an environment that you are already familiar and comfortable with.
machine-learning artificial-intelligence neural-network computation-graph differentiation gradient-descent gorgonia deep-learning deeplearning deep-neural-networks automatic-differentiation symbolic-differentiation go-libraryPyTorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
PyTorch is a deep learning framework that puts Python first. It is a python package that provides Tensor computation (like numpy) with strong GPU acceleration, Deep Neural Networks built on a tape-based autograd system. You can reuse your favorite python packages such as numpy, scipy and Cython to extend PyTorch when needed.
neural-network autograd gpu numpy deep-learning tensordeepvariant - DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.DeepVariant is a suite of Python/C++ programs that run on any Unix-like operating system. For convenience the documentation refers to building and running DeepVariant on Google Cloud Platform, but the tools themselves can be built and run on any standard Linux computer, including on-premise machines. Note that DeepVariant currently requires Python 2.7 and does not yet work with Python 3.
tensorflow deep-neural-network genomics science dna sequencing genome bioinformatics deep-learning ngs deepvariant machine-learningtangent - Source-to-Source Debuggable Derivatives in Pure Python
Tangent is a new, free, and open-source Python library for automatic differentiation.Existing libraries implement automatic differentiation by tracing a program's execution (at runtime, like PyTorch) or by staging out a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools.
autodiff automatic-differentiation machine-learning deep-learningForge - A neural network toolkit for Metal
Forge is a collection of helper code that makes it a little easier to construct deep neural networks using Apple's MPSCNN framework. Conversion functions. MPSCNN uses MPSImages and MTLTextures for everything, often using 16-bit floats. But you probably want to work with Swift [Float] arrays. Forge's conversion functions make it easy to work with Metal images and textures.
metal deep-learning deep-neural-networks neural-network ios mobilenets machine-learningtensorflow_template_application - TensorFlow template application for deep learning
It is the generic golden program for deep learning with TensorFlow.Following are the supported features.
tensorflow tfrecords libsvm csv deep-learning machine-learning mlp cnn lstm classifier recommendation-system cpp spark grpc android mavenincubator-mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Apache MXNet (incubating) is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines.MXNet is also more than a deep learning project. It is also a collection of blue prints and guidelines for building deep learning systems, and interesting insights of DL systems for hackers.
deep-learning deep-neural-networks mxnet distributed-systems machine-learning artificial-intelligencepytorch-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 tensorboardnnvm - Bring deep learning to bare metal
The following code snippet demonstrates the general workflow of nnvm compiler.Licensed under an Apache-2.0 license.
computation-graph deep-learning optimization deployment nnvm tvm cuda opencl rocm metalDeepSpeech - 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-textdata-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines
IPython Notebook(s) demonstrating deep learning functionality.IPython Notebook(s) demonstrating scikit-learn functionality.
machine-learning deep-learning data-science big-data aws tensorflow theano caffe scikit-learn kaggle spark mapreduce hadoop matplotlib pandas numpy scipy kerasELF - An End-To-End, Lightweight and Flexible Platform for Game Research
ELF is an Extensive, Lightweight and Flexible platform for game research, in particular for real-time strategy (RTS) games. On the C++-side, ELF hosts multiple games in parallel with C++ threading. On the Python side, ELF returns one batch of game state at a time, making it very friendly for modern RL. In comparison, other platforms (e.g., OpenAI Gym) wraps one single game instance with one Python interface. This makes concurrent game execution a bit complicated, which is a requirement of many modern reinforcement learning algorithms. Besides, ELF now also provides a Python version for running concurrent game environments, by Python multiprocessing with ZeroMQ inter-process communication. See ./ex_elfpy.py for a simple example.
gaming cpp artificial-intelligence deep-learning neural-network platform reinforcement-learningneuralconvo - Neural conversational model in Torch
This is an attempt at implementing Sequence to Sequence Learning with Neural Networks (seq2seq) and reproducing the results in A Neural Conversational Model (aka the Google chatbot). Human: What is the purpose of living? Machine: To live forever.
seq2seq torch machine-learning deep-learning neural-conversation-modelsawesome-artificial-intelligence - A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers. Contributions most welcome.
machine-learning machine-intelligence artificial-intelligence reinforcement-learning intelligent-systems deep-learning intelligent-machinesufldl_tutorial - Stanford Unsupervised Feature Learning and Deep Learning Tutorial
Stanford Unsupervised Feature Learning and Deep Learning Tutorial
deep-learning deep-learning-tutorial convolutional-neural-networksnolearn - Combines the ease of use of scikit-learn with the power of Theano/Lasagne
nolearn contains a number of wrappers and abstractions around existing neural network libraries, most notably Lasagne, along with a few machine learning utility modules. All code is written to be compatible with scikit-learn. We recommend using venv (when using Python 3) or virtualenv (Python 2) to install nolearn.
scikit-learn lasagne deep-learning machine-learningopencv - Open Source Computer Vision Library
Please read the contribution guidelines before starting work on a pull request.
opencv c-plus-plus computer-vision deep-learning image-processing
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