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Found 7 result(s)

UC Irvine Machine Learning Repository

UCI Machine Learning Repository

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The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.

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.

Scientific Data Repository

Data Repository. Interactive Analytics, Exploration & Visualization.

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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.

Social Computing Data Repository

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Social Computing Data Repository hosts data from a collection of many different social media sites, most of which have blogging capacity. Some of the prominent social media sites included in this repository are BlogCatalog, Twitter, MyBlogLog, Digg, StumbleUpon, del.icio.us, MySpace, LiveJournal, The Unofficial Apple Weblog (TUAW), Reddit, etc. The repository contains various facets of blog data including blog site metadata like, user defined tags, predefined categories, blog site description; blog post level metadata like, user defined tags, date and time of posting; blog posts; blog post mood (which is defined as the blogger's emotions when (s)he wrote the blog post); blogger name; blog post comments; and blogger social network.

Network Repository

Network Data Repository, Graph Data, Social Networks

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Network Repository is the first interactive data repository for graph and network data. It hosts graph and network datasets, containing hundreds of real-world networks and benchmark datasets. Unlike other data repositories, Network Repository provides interactive analysis and visualization capabilities to allow researchers to explore, compare, and investigate graph data in real-time on the web.

ColabFit Exchange

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The ColabFit Exchange is an online resource for the discovery, exploration and submission of datasets for data-driven interatomic potential (DDIP) development for materials science and chemistry applications. ColabFit's goal is to increase the Findability, Accessibility, Interoperability, and Reusability (FAIR) of DDIP data by providing convenient access to well-curated and standardized first-principles and experimental datasets. Content on the ColabFit Exchange is open source and freely available.

AIDA Data Hub

AIDA Dataset Register

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The AIDA data hub is a place where researchers can collaboratively gather, annotate, share and enrich large volumes of research data for machine learning in medical imaging diagnostics.