for Scalable and Reliable Machine Learning

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Who We Are

DMLC is a group to collaborate on open-source machine learning projects, with a goal of making cutting-edge large-scale machine learning widely available. The contributors includes researchers, PhD students and data scientists who are actively working on the field.

Machine Learning Libraries

MXNet


Flexible and Efficient Deep Learning Library on Heterogeneous Distributed Systems

XGBoost

General purpose gradient boosting library, including generalized linear model and gradient boosted decision trees

Minerva

NDarray programming interface (like Numpy) for deep learning


System Components

dmlc-core

Data I/O for filesystems such as HDFS and Amazon S3, with job launchers for Yarn, MPI, ...

ps-lite

The parameter server framework for asynchronous key-value push and pull

Rabit

A light weight library providing fault tolerant Allreduce and Broadcast

mshadow

A lightweight CPU/GPU Matrix/Tensor Template Library.


Acknowledgment


We sincerely thank the following organizations (alphabetical order) for sponsoring the major developers of DMLC

               

and supporting the DMLC projects