mlpack: a scalable C++ machine learning library --

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.3.1) mlpack is an intuitive, fast, and flexible C++ machine le

Related Repos

facebookincubator Gloo Gloo is a collective communications library. It comes with a number of collective algorithms useful for machine learning applications. These include a barrier, broadcast, and allreduce. Transport of data between participa

eveningglow Age and Gender Classification using Convolutional Neural Network Implementation of paper Age and Gender Classification using Convolutional Neural Network (June, 2015) using caffe. Requisites 1. Caffe (Deep Learning Li

tobegit3hub MiniFlow Introduction MiniFlow is the numerical computation library which implements TensorFlow APIs. Support math calculations and composited operations Support automatic partial derivative and chain rule Supp

sony Neural Network Libraries Neural Network Libraries is a deep learning framework that is intended to be used for research, development and production. We aim to have it running everywhere: desktop PCs, HPC clusters, embedded device

davisking dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. See for the main project documentation and API

Microsoft Embedded Learning Library The Embedded Learning Library (ELL) allows you to design and deploy intelligent machine-learned models onto resource constrained platforms and small single-board computers, like Raspberry Pi, Arduino, an

Svalorzen AI-Toolbox This C++ toolbox is aimed at representing and solving common AI problems, implementing an easy-to-use interface which should be hopefully extensible to many problems, while keeping code readable. Current develo

odashi NMTKit (Japanese version is here) NMTKit is a neural network-based statistical machine translation toolkit. This toolkit is written by C++, and the main computation architecture is based on DyNet v1.1. To get started, see files