# DMTK

**Repository Path**: strongandyzhang/DMTK

## Basic Information

- **Project Name**: DMTK
- **Description**: Microsoft Distributed Machine Learning Toolkit
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-02-20
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## 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 [dmtk@microsoft.com](mailto:dmtk@microsoft.com)

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 [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.