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Found 5 result(s)

SMU Research Data Repository

Singapore Management University Research Data Repository

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SMU Research Data Repository (SMU RDR) is a tool and service for researchers from Singapore Management University (SMU) to store, share and publish their research data. SMU RDR accepts a wide range of research data and outputs generated from research projects.

IIT Dataverse

Italian Institute of Technology Dataverse

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IIT Dataverse is the institutional research data repository of the Istituto Italiano di Tecnologia. IIT Dataverse has been operative since May 2021 and is currently open to IIT-affiliated researchers for research data deposition and sharing.

University of Salford Data Repository

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Figshare is the University of Salford Data Repository for archiving and publishing research data, in accordance with EPSRC expectations, and to increase the impact of the research.

Propylaeum@heiDATA

Data publications of the Specialized Information Service Classics

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Additional to the the e-publishing offer for articles, books and journals, Propylaeum provides classical scholars with the opportunity to archive the respective research data permanently. These can be linked directly to online publications hosted on the Heidelberg publishing platforms. All research data – e.g. images, videos, audio files, tables, graphics etc. – receive a DOI (Digital Object Identifiyer). Thus, they can be cited, viewed and permanently linked to as distinct academic output.

OpenML

Open Machine Learning

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OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.