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Found 7 result(s)
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.
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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.
The Registry of Open Data on AWS provides a centralized repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge to their users. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users.
The University of Guelph Research Data Repositories provide long-term stewardship of research data created at or in cooperation with the University of Guelph. The Data Repositories are guided by the FAIR Guiding Principles for scientific data management and stewardship which aim to improve the Findability, Accessibility, Interoperability and Reuse of research data. The Data Repositories is composed of two main collections: the Agri-environmental Research Data collection which houses agricultural and environmental research data, and the Cross-disciplinary Research Data collection which houses all other disciplinary research data.
This repository stores and links the openly available power-grid frequency recordings across the globe. This database is comprised of open data existent across three dimensions: - TSO data: Transmission System's Operator (TSO) recordings made public; - Research projects: Open-data database research projects; - Independent Gatherings: Industrial, private, or personal recordings that were made publicly available.
Research Data Repository of the Instituto Federal Goiano - Campus Urutaí, a Brazilian public institution of the Ministry of Education. The project is an initiative of the Directorate of Post-Graduate Studies, Research and Innovation of the Federal Institute of Goiás - Campus Urutaí, which follows the philosophy of Open Science, for expansion and valuation of scientific research, aiming to provide data from technical-scientific observations and experimentation, ensuring that its authors, researchers and students receive all the credit they deserve as agents generating data. At the same time, the appropriate reuse of data is envisaged, whether in didactic-pedagogical activities or in new research.