{"id":13749828,"url":"https://github.com/Microsoft/DMTK","last_synced_at":"2025-05-09T13:30:52.141Z","repository":{"id":65975361,"uuid":"45765537","full_name":"microsoft/DMTK","owner":"microsoft","description":"Microsoft Distributed Machine Learning Toolkit","archived":true,"fork":false,"pushed_at":"2018-09-12T21:14:58.000Z","size":17,"stargazers_count":2749,"open_issues_count":1,"forks_count":558,"subscribers_count":305,"default_branch":"master","last_synced_at":"2025-05-07T23:46:43.245Z","etag":null,"topics":["dmtk","lightgbm","machine-learning","microsoft","multiverso"],"latest_commit_sha":null,"homepage":"http://www.dmtk.io","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/microsoft.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-11-08T03:32:50.000Z","updated_at":"2025-03-22T19:32:16.000Z","dependencies_parsed_at":"2023-02-19T18:45:17.850Z","dependency_job_id":null,"html_url":"https://github.com/microsoft/DMTK","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/microsoft%2FDMTK","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/microsoft%2FDMTK/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/microsoft%2FDMTK/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/microsoft%2FDMTK/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/microsoft","download_url":"https://codeload.github.com/microsoft/DMTK/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253258136,"owners_count":21879595,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["dmtk","lightgbm","machine-learning","microsoft","multiverso"],"created_at":"2024-08-03T07:01:14.066Z","updated_at":"2025-05-09T13:30:51.864Z","avatar_url":"https://github.com/microsoft.png","language":null,"readme":"\n# DMTK\n\nDistributed Machine Learning Toolkit [https://www.dmtk.io](https://www.dmtk.io)\nPlease open issues in the project below. For any technical support email to [dmtk@microsoft.com](mailto:dmtk@microsoft.com)\n\nDMTK includes the following projects:\n* [DMTK framework(Multiverso)](https://github.com/Microsoft/multiverso): The parameter server framework for distributed machine learning.\n* [LightLDA](https://github.com/Microsoft/lightlda): Scalable, fast and lightweight system for large-scale topic modeling.\n* [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. \n* [Distributed word embedding](https://github.com/Microsoft/multiverso/tree/master/Applications/WordEmbedding): Distributed algorithm for word embedding implemented on multiverso.\n\n\n\n# Updates\n## 2017-02-04\n* 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).\n\n## 2016-11-21 \n* [Multiverso](https://github.com/Microsoft/multiverso) has been officially used in Microsoft [CNTK](https://github.com/microsoft/cntk) to power its ASGD parallel training.  \n\n## 2016-10-17 \n* [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. \n\n## 2016-09-12\n* 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). \n\n## 2016-07-05 \n* Multiverso has been upgrade to new API.[Overview](https://github.com/Microsoft/multiverso/wiki/Overview)\n* 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.\n* 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).\n\n\n\nMicrosoft Open Source Code of Conduct\n------------\n\nThis 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.\n","funding_links":[],"categories":["Researchers","Distributed Computing","Others","Table of Contents","IoT 笔记"],"sub_categories":["Frameworks","Synthetic Data","NLP","人工智能"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMicrosoft%2FDMTK","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FMicrosoft%2FDMTK","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMicrosoft%2FDMTK/lists"}