{"id":171314,"date":"2014-03-21T14:26:11","date_gmt":"2014-03-21T14:26:11","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/project\/codalab\/"},"modified":"2019-08-19T14:32:28","modified_gmt":"2019-08-19T21:32:28","slug":"codalab","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/codalab\/","title":{"rendered":"CodaLab"},"content":{"rendered":"

CodaLab is an open-source web-based platform that enables researchers, developers, and data scientists to collaborate, with the goal of advancing research fields where machine learning and advanced computation is used. CodaLab helps solve many common problems in the arena of data-oriented research through its online community, where people share worksheets and participate in collaborative competitions.<\/p>\n

Immutable experimentation that ensures reproducibility<\/h2>\n

Today\u2019s data-driven research and development is stymied by an inability of scientists and their collaborators to easily reproduce and augment one another\u2019s experiments. CodaLab addresses this problem by providing a cloud-based virtual \u201cworkbench,\u201d where computer scientists can conduct data-driven experiments quickly and easily.<\/p>\n

Experiments can then be easily copied, reworked, and edited by other collaborators in order to advance the state-of-the-art in data-driven research and machine learning. Conferences such as ACL 2016 encourage the use of CodaLab Worksheets for submission of software resources with papers. Do you want to share your research and accelerate the path of innovation?<\/p>\n

Try CodaLab Worksheets now (opens in new tab)<\/span><\/a>\u00a0><\/p>\n

Collaboration that drives innovation<\/h2>\n

By working with the data-driven research community, we have enhanced the ability of scientists and engineers to organize and host competitions in which participants can collaborate with one another to deliver the best solutions for some of their most challenging problems.<\/p>\n

Try CodaLab Competitions\u00a0now (opens in new tab)<\/span><\/a>\u00a0><\/p>\n

Want to further develop CodaLab?<\/strong>
\nContribute to this open-source platform on GitHub (opens in new tab)<\/span><\/a>\u00a0><\/p><\/blockquote>\n

Community partners<\/h2>\n

CodaLab’s community leaders include Percy Liang (opens in new tab)<\/span><\/a>, of Stanford University (opens in new tab)<\/span><\/a>, who focuses on CodaLab Worksheets (opens in new tab)<\/span><\/a>; Isabelle Guyon (opens in new tab)<\/span><\/a>, of University of Paris-Saclay (opens in new tab)<\/span><\/a> and ChaLearn (opens in new tab)<\/span><\/a>, who focuses on CodaLab Competitions (opens in new tab)<\/span><\/a>; and Sergio Escalera (opens in new tab)<\/span><\/a>, of the Autonomous University of Barcelona (opens in new tab)<\/span><\/a>.<\/p>\n

Acknowledgments<\/h2>\n

CodaLab has received important contributions from many people, and we would like to thank them for their efforts in making CodaLab what it is today:<\/p>\n

Pujun Bhatnagar, Eric Carmichael, Justin Carden, Richard Caruana, Francis Cleary, Sergio Escalera, Ivan Judson, Lori Ada Kilty, Shaunak Kishore, Stephen Koo, Pragnya Maduskar, Simon Mercer, Arthur Pesah, Christophe Poulain<\/a>, Lukasz Romaszko, Xavier Baro Sole, Paul Viola, Erick Watson, Tony Yang, Flavio Zhingri, Michael Zyskowski.<\/p>\n","protected":false},"excerpt":{"rendered":"

CodaLab is an open-source web-based platform that enables researchers, developers, and data scientists to collaborate, with the goal of advancing research fields where machine learning and advanced computation is used. CodaLab helps solve many common problems in the arena of data-oriented research through its online community, where people share worksheets and participate in collaborative competitions. […]<\/p>\n","protected":false},"featured_media":236051,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556,13562,13545],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-171314","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-research-area-computer-vision","msr-research-area-human-language-technologies","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"2014-03-21","related-publications":[],"related-downloads":[],"related-videos":[191118,191185],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[{"id":0,"name":"Events","content":"