https://github.com/microsoft/DMTK

Microsoft Distributed Machine Learning Toolkit
https://github.com/microsoft/DMTK

dmtk lightgbm machine-learning microsoft multiverso

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Microsoft Distributed Machine Learning Toolkit

• Host: GitHub
• URL: https://github.com/microsoft/DMTK
• Owner: microsoft
• License: mit
• Archived: true
• Created: 2015-11-08T03:32:50.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2018-09-12T21:14:58.000Z (about 6 years ago)
• Last Synced: 2024-08-06T20:07:58.517Z (3 months ago)
• Topics: dmtk, lightgbm, machine-learning, microsoft, multiverso
• Homepage: http://www.dmtk.io
• Size: 16.6 KB
• Stars: 2,745
• Watchers: 309
• Forks: 560
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        

# DMTK

Distributed Machine Learning Toolkit [https://www.dmtk.io](https://www.dmtk.io)

Please open issues in the project below. For any technical support email to [[email protected]](mailto:[email protected])

DMTK includes the following projects:

* [DMTK framework(Multiverso)](https://github.com/Microsoft/multiverso): The parameter server framework for distributed machine learning.

* [LightLDA](https://github.com/Microsoft/lightlda): Scalable, fast and lightweight system for large-scale topic modeling.

* [LightGBM](https://github.com/Microsoft/lightGBM): LightGBM is a fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. 

* [Distributed word embedding](https://github.com/Microsoft/multiverso/tree/master/Applications/WordEmbedding): Distributed algorithm for word embedding implemented on multiverso.

# Updates

## 2017-02-04

* A tutorial on the latests updates of Distributed Machine Learning is presented on [AAAI 2017](https://www.aaai.org/Conferences/AAAI/aaai17.php). you can download the slides [here](https://www.dmtk.io/tutorial_on_aaai2017.html).

## 2016-11-21 

* [Multiverso](https://github.com/Microsoft/multiverso) has been officially used in Microsoft [CNTK](https://github.com/microsoft/cntk) to power its ASGD parallel training.  

## 2016-10-17 

* [LightGBM](https://github.com/Microsoft/lightGBM) has been released. which is a fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. 

## 2016-09-12

* A talk on the latest updates of DMTK is presented on [GTC China](http://www.gputechconf.cn/page/home.html). We also described the latest research work from our team, including the lightRNN(to be appeared in NIPS2016) and [DC-ASGD](https://arxiv.org/abs/1609.08326). 

## 2016-07-05 

* Multiverso has been upgrade to new API.[Overview](https://github.com/Microsoft/multiverso/wiki/Overview)

* Deep learning framework ([torch](https://github.com/Microsoft/multiverso/wiki/Multiverso-Torch-Binding-Benchmark)/[theano](https://github.com/Microsoft/multiverso/wiki/Multiverso-Python-Binding-Benchmark)) support has been added.

* Python/Lua bidding has been supported, you can using multiverso with [Python](https://github.com/Microsoft/multiverso/wiki/Multiverso-Python-Theano-Lasagne-Binding)/[Lua](https://github.com/Microsoft/multiverso/wiki/Multiverso-Torch-Lua-Binding).

Microsoft Open Source Code of Conduct

------------

This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or contact [[email protected]](mailto:[email protected]) with any additional questions or comments.