Displaying 1 to 20 from 20 results

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-computationMXNet 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-intelligenceThe 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 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 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-libraryProject 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.Pre-built binaries can be found on TaskCluster. You'll need to download native_client.tar.xz and the appropriate Python wheel package.

deep-learning machine-learning neural-networks tensorflow speech-recognition speech-to-textConvNetJS is a Javascript implementation of Neural networks, It currently supports Common Neural Network modules, Classification (SVM/Softmax) and Regression (L2) cost functions, A MagicNet class for fully automatic neural network learning (automatic hyperparameter search and cross-validatations), Ability to specify and train Convolutional Networks that process images, An experimental Reinforcement Learning module, based on Deep Q Learning.

artificial-intelligence neural-networks machine-learning deep-learningDeepDetect is an Instant Machine Learning for your Applications. It can classify images, text and numerical data from your application or the command line by series of simple calls to the deep learning server. A simple yet powerful and generic API for use of Machine Learning.

artificial-intelligence neural-networks machine-learning deep-learningCaffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and by community contributors.

artificial-intelligence neural-networks machine-learning deep-learningTheano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy. Its features include tight integration with NumPy, transparent use of a GPU, dynamic C code generation and lot more.

deep-learning neural-network math numerical symbolic blas numpy gpu autodiff differentiationH2O is for data scientists and application developers who need fast, in-memory scalable machine learning for smarter applications. H2O is an open source parallel processing engine for machine learning. Unlike traditional analytics tools, H2O provides a combination of extraordinary math, a high performance parallel architecture, and unrivaled ease of use.

artificial-intelligence neural-networks machine-learning deep-learning numerical-computationDSSTNE (pronounced "Destiny") is an open source software library for training and deploying recommendation models with sparse inputs, fully connected hidden layers, and sparse outputs. Models with weight matrices that are too large for a single GPU can still be trained on a single host. DSSTNE has been used at Amazon to generate personalized product recommendations for our customers at Amazon's scale.

deep-learning neural-networks artificial-intelligence personalizationSonnet is a library built on top of TensorFlow for building complex neural networks. The library uses an object-oriented approach, similar to Torch/NN, allowing modules to be created which define the forward pass of some computation. Modules are called with some input Tensors, which adds ops to the Graph and returns output Tensors.

neural-networks artificial-intelligence deep-learningDeeplearning4J is an open source, distributed neural net library written in Java and Scala. It integrates with Hadoop and Spark and runs on several backends that enable use of CPUs and GPUs. It provides versatile n-dimensional array class for Java and Scala.

deep-learning neural-network numerical scientific artificial-intelligenceGym StarCraft is an environment bundle for OpenAI Gym. It is based on Facebook's TorchCraft, which is a bridge between Torch and StarCraft for AI research.Install OpenAI Gym and its dependencies.

openai-gym gym-starcraft starcraft reinforcement-learning artificial-intelligence deep-learningImplementation of document classification model described in Hierarchical Attention Networks for Document Classification (Yang et al., 2016).I am getting 65% accuracy on a dev set (16% of data) after 3 epochs. Results reported in the paper are 71% on Yelp'15. No systemic hyperparameter optimization was performed.

document-classification hierarchical-attention-networks tensorflow deep-learning nlp machine-learningThis project is an experimental wrapper of TensorFlow C API which enables Machine Learning in Server Side Swift.This package builds with Swift Package Manager and is part of the Perfect project but can also be used as an independent module.

machine-learning artificial-intelligence artificial-neural-networks swift perfect matrix-library tensorflow deep-learningHorovod is a distributed training framework for TensorFlow. The goal of Horovod is to make distributed Deep Learning fast and easy to use.Internally at Uber we found that it's much easier for people to understand an MPI model that requires minimal changes to source code than to understand how to set up regular Distributed TensorFlow.

tensorflow uber machine-learning machinelearning mpi baidu deep-learning deeplearningRecent results in Bayesian statistics for constructing robust neural networks have proved that it is one of the best ways to deal with uncertainty, overfitting but still having good performance. Gelato will help to use bayes for neural networks. Library heavily relies on Theano, Lasagne and PyMC3.I use generic approach for decorating all Lasagne at once. Thus, for using Gelato you need to replace import statements for layers only. For constructing a network you need to be the in pm.Model context environment.

bayesian-inference lasagne uncertainty variational-inference gelato neural-network theano deep-learning bayesianThe Data Science Virtual Machine (DSVM) is a customized VM image on Microsoft’s Azure cloud built specifically for doing data science. It has many popular data science and other tools pre-installed and pre-configured to jump-start building intelligent applications for advanced analytics. It is available on Windows Server 2016, Windows Server 2012, and on Linux. We offer Linux edition of the DSVM in either Ubuntu 16.04 LTS or on OpenLogic 7.2 CentOS-based Linux distributions. You can try the Data Science VM for free for 30 days (with $200 credits) with a free Azure Trial. The Linux (Ubuntu-based) DSVM also provides a test drive through a button on the product page. The Test Drive will provide full access to you own instance of the VM with just a free Microsoft account (No Azure subscription or CC needed).On this repo, we will feature tools, tips and extensions (see below) to the Data Science VM. We invite the DSVM user community to contribute any useful tools or scripts, extensions you may have written to enhance the user experience on the DSVM.

data-science data-analysis machine-learning deep-learning azure big-data ai ml dsvm r sqlserver