A Community of Awesome Machine Learning Projects
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L'organizzazione dmlc su GitHub è una comunità dedicata ai progetti di machine learning distribuito e profondo. Con una vasta gamma di repository, dmlc utilizza linguaggi di programmazione come C++, Python e Jupyter Notebook. Tra i progetti più noti ci sono xgboost, dgl e gluon-cv, che supportano diversi framework di deep learning.
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, Dask, Flink and DataFlow
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Gluon CV Toolkit
NLP made easy
An efficient video loader for deep learning with smart shuffling that's super easy to digest
Nessuna descrizione fornita per questo repository.
A lightweight parameter server interface
common in-memory tensor structure
Matrix Shadow:Lightweight CPU/GPU Matrix and Tensor Template Library in C++/CUDA for (Deep) Machine Learning
NumPy interface with mixed backend execution
move forward to https://github.com/dmlc/mxnet
A common bricks library for building scalable and portable distributed machine learning.
Universal model exchange and serialization format for decision tree forests
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.
moved to https://github.com/dmlc/ps-lite
Notebooks for MXNet
Reliable Allreduce and Broadcast Interface for distributed machine learning
MXNetJS: Javascript Package for Deep Learning in Browser (without server)
Standalone TensorBoard for visualizing in deep learning
MXNet Julia Package - flexible and efficient deep learning in Julia
Deprecated
Sublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets
XGBoost Julia Package
Distributed Factorization Machines
Pre-trained Models of DMLC Project
Visualization tool for Graph Neural Networks
Symbolic Expression and Statement Module for new DSLs
MXNet Tutorial for NVidia GTC 2016.
Nessuna descrizione fornita per questo repository.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on MXNet, Theano or TensorFlow.
C++ interface for mxnet
cache-friendly multithread matrix factorization
The repo to host all the web data including images for documents in dmlc projects.
Kernel Fusion and Runtime Compilation Based on NNVM
TL2cgen (TreeLite 2 C GENerator) is a model compiler for decision tree models
Nessuna descrizione fornita per questo repository.
Nessuna descrizione fornita per questo repository.
Host custom actions; keep track of manual approval requests for CI jobs.
Caffe: a fast open framework for deep learning.
Benchmark speed and other issues internally, before push to deep-mark
MXNet Example
Machine learning, in numpy
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Drat Repository for DMLC R packages
Nessuna descrizione fornita per questo repository.
ccache – a fast compiler cache
Nessuna descrizione fornita per questo repository.
Optimized primitives for collective multi-GPU communication
Nessuna descrizione fornita per questo repository.
redirect mxnet.readthedocs.io to mxnet.io
Nessuna descrizione fornita per questo repository.
dmlc sviluppa una varietà di strumenti e librerie per il machine learning, inclusi progetti come xgboost per il boosting gradiente e dgl per l'apprendimento profondo sui grafi.
L'organizzazione dmlc utilizza principalmente linguaggi come C++, Python, Jupyter Notebook, Cuda, JavaScript e Julia per sviluppare i suoi progetti su GitHub.
Sì, tutti i repository di dmlc su GitHub sono pubblici, consentendo agli sviluppatori di accedere e contribuire a progetti come gluon-cv e decord.
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