Distributed (Deep) Machine Learning Community

tvm

Open deep learning compiler stack for cpu, gpu and specialized accelerators

gluon-cv

Gluon CV Toolkit

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

web-data

The repo to host all the web data including images for documents in dmlc projects.

gluon-nlp

NLP made easy

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dmlc-core

A common bricks library for building scalable and portable distributed machine learning.

MXNet.jl

MXNet Julia Package - flexible and efficient deep learning in Julia

rabit

Reliable Allreduce and Broadcast Interface for distributed machine learning

ps-lite

A lightweight parameter server interface

dlpack

RFC for common in-memory tensor structure and operator interface for deep learning system

HalideIR

Symbolic Expression and Statement Module for new DSLs

tensorboard

Standalone TensorBoard for visualizing in deep learning

XGBoost.jl

XGBoost Julia Package

treelite

model compiler for decision tree ensembles

mshadow

Matrix Shadow:Lightweight CPU/GPU Matrix and Tensor Template Library in C++/CUDA for (Deep) Machine Learning

minerva

Minerva: a fast and flexible tool for deep learning on multi-GPU. It provides ndarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy.

nnvm

move to https://github.com/dmlc/tvm/

dmlc.github.io

the homepage http://dmlc.ml

mxnet.js

MXNetJS: Javascript Package for Deep Learning in Browser (without server)

minpy

NumPy interface with mixed backend execution

mxnet-notebooks

Notebooks for MXNet

drat

Drat Repository for DMLC R packages

mxnet-memonger

Sublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets

cub

nn-examples

MXNet.cpp

C++ interface for mxnet