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Found 4 result(s)

Kaggle

Your home for data science

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Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.

RWTH Publications Research Data

RWTH Publications Forschungsdaten

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RWTH Publications Research Data offers all RWTH Aachen University affiliates the organizational and technical means to electronically document and publish research data at this institutional repository. Certainly, researchers are encouraged to prefer a subject specific repository whenever appropriate and available. RWTH Aachen University is the largest technical university in Germany and one of nine 'German Universities of Excellence' (elite university). The University library Aachen operates the repository as a member of the join community.

ECHO – Cultural Heritage Online

Open Access Infrastructure for a Future Web of Culture and Science

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The ECHO initiative aims to create an infrastructure to bring cultural heritage on the Internet, and builds up a network of institutions, research projects and other users which provide content and technology for the common infrastructure, with the aim to enrich the "agora" and to create a future Web of Culture and Science.

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.