Distributed (Deep) Machine Learning Community
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Pinned repositories
Repositories
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dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
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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
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treelite
model compiler for decision tree ensembles
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gluon-nlp
NLP made easy
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gluon-cv
Gluon CV Toolkit
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web-data
The repo to host all the web data including images for documents in dmlc projects.
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dmlc-core
A common bricks library for building scalable and portable distributed machine learning.
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rabit
Reliable Allreduce and Broadcast Interface for distributed machine learning
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decord
An efficient video loader for deep learning with smart shuffling that's super easy to digest
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ps-lite
A lightweight parameter server interface
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XGBoost.jl
XGBoost Julia Package
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dlpack
RFC for common in-memory tensor structure and operator interface for deep learning system
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HalideIR
Symbolic Expression and Statement Module for new DSLs
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tensorboard Archived
Standalone TensorBoard for visualizing in deep learning
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mshadow Archived
Matrix Shadow:Lightweight CPU/GPU Matrix and Tensor Template Library in C++/CUDA for (Deep) Machine Learning
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MXNet.jl
MXNet Julia Package - flexible and efficient deep learning in Julia
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minerva Archived
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.
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keras
Forked from keras-team/kerasDeep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on MXNet, Theano or TensorFlow.
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mxnet.js
MXNetJS: Javascript Package for Deep Learning in Browser (without server)
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minpy Archived
NumPy interface with mixed backend execution
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mxnet-notebooks
Notebooks for MXNet
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drat
Drat Repository for DMLC R packages
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mxnet-memonger
Sublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets