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WorldData.AI comes with a built-in workspace – the next-generation hyper-computing platform powered by a library of 3.3 billion curated external trends. WorldData.AI allows you to save your models in its “My Models Trained” section. You can make your models public and share them on social media with interesting images, model features, summary statistics, and feature comparisons. Empower others to leverage your models. For example, if you have discovered a previously unknown impact of interest rates on new-housing demand, you may want to share it through “My Models Trained.” Upload your data and combine it with external trends to build, train, and deploy predictive models with one click! WorldData.AI inspects your raw data, applies feature processors, chooses the best set of algorithms, trains and tunes multiple models, and then ranks model performance.
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Standard, reference material is used for measurement process control and reliability evaluation of measurement results, and plays a key role in important fields such as food safety, international and domestic trade, medicine and health, and environmental monitoring. In order to realize the efficient use and sharing of reference material resources in the whole society, the Institute of Chemistry of China Institute of Metrology (formerly the National Reference Material Research Center), with the support of the Ministry of Science and Technology, launched the "National Reference Material Information Service" at the end of 2003.
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
The Minnesota Population Center (MPC) is a University-wide interdisciplinary cooperative for demographic research. The MPC serves more than 80 faculty members and research scientists from eight colleges and institutes at the University of Minnesota. As a leading developer and disseminator of demographic data, we also serve a broader audience of some 50,000 demographic researchers worldwide. MPC is a DataONE member node: https://search.dataone.org/#profile/US_MPC