Displaying 1 to 20 from 64 results

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.

CNTK - 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.

gorgonia - 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.

IAMDinosaur - 🦄 An Artificial Inteligence to teach Google's Dinosaur to jump cactus

A simple artificial intelligence to teach Google Chrome's offline dinosaur to jump cactus, using Neural Networks and a simple Genetic Algorithm.Install Node.js on your computer.

incubator-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.

ELF - 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.

fairseq-py - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

This is a PyTorch version of fairseq, a sequence-to-sequence learning toolkit from Facebook AI Research. The original authors of this reimplementation are (in no particular order) Sergey Edunov, Myle Ott, and Sam Gross. The toolkit implements the fully convolutional model described in Convolutional Sequence to Sequence Learning and features multi-GPU training on a single machine as well as fast beam search generation on both CPU and GPU. We provide pre-trained models for English to French and English to German translation. Currently fairseq-py requires PyTorch version >= 0.3.0. Please follow the instructions here: https://github.com/pytorch/pytorch#installation.

nupic - Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex

The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources. For more information, see numenta.org or the NuPIC Forum. For usage guides, quick starts, and API documentation, see http://nupic.docs.numenta.org/.

TensorFlow - 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.

Snake - Artificial intelligence of the Snake game.

This project focuses on the artificial intelligence of the Snake game. The snake's goal is to eat the food continuously and fill the map with its bodies ASAP. The old version of this project is written in C++. Now it has been rewritten using Python for a user-friendly GUI and the simplicity in the implementations of algorithms. Requirements: Python 3.5+ with Tkinter installed.

shogun - Shōgun

Unified and efficient Machine Learning since 1999. Buildbot: http://buildbot.shogun-toolbox.org/waterfall.

DeepDetect - Deep Learning Server

DeepDetect 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.

H2O - Fast Scalable Machine Learning API For Smarter Applications

H2O 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.

Mycroft - an Artificial intelligence for everyone

Mycroft is an Artificial intelligence for everyone. It uses open software to process natural language, determine your intent and take action. It can integrate a host of professional functions – Control scenes to conserve power, grant office access with your voice. It can control all of your media and devices with the sound of your voice. Adjust your thermostat, turn on your lights, water your lawn, play your favorite movie and lot more.

Amazon DSSTNE: Deep Scalable Sparse Tensor Network Engine

DSSTNE (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.

Sonnet - Library built on top of TensorFlow for building complex neural networks

Sonnet 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.

Abot - Digital Assistant Framework

Abot (pronounced Eh-Bot, like the Canadians) is a digital assistant framework that enables anyone to easily build a digital assistant similar to Apple's Siri, Microsoft's Cortana, Google Now, or Amazon Alexa. Further, Abot supports a human-aided training backend enabling anyone to build services like Facebook M. Abot is the first A.I. framework that aims to be available everywhere and— ultimately—to do everything.