NSF Unidata 2024 Community Equipment Awards: Deadline Extended
04 March 2024
As a result of changes in the spring 2024 meeting schedule for the NSF Unidata Users Committee, we are able to extend the submission deadline for this year's Community Equipment Awards solicitation until March 29, 2024. All other aspects of the 2024 program remain as described in the original announcement.
[Read More]04 March 2024
K Nearest Neighbors (KNN) is a supervised machine learning method that 'memorizes' (stores) an entire dataset, then relies on the concepts of proximity and similarity to make predictions about new data. The basic idea is that if a new data point is in some sense 'close' to existing data points, its value is likely to be similar to the values of its neighbors. In the Earth Systems Sciences, such techniques can be useful for small- to moderate-scale classification and regression problems.
[Read More]AWIPS Tips: AWIPS 20.3.2-2 Software Release
21 February 2024
Welcome back to AWIPS Tips!
We are excited to announce our release of 20.3.2-2 that incorporates many updates and fixes from the 20.3.2-1 release. This release includes installers for CAVE (CentOS7, Windows, VMware Player, and MacOS), and for EDEX (CentOS7).
[Read More]AMS 2024 Conference Highlights from the NSF Unidata Staff
14 February 2024
This year's annual American Meteorological Society meeting was held 27 January - 1 February 2024 in Baltimore, MD. Several NSF Unidata staff members were able to travel to Baltimore to lead workshops, visit with students, present papers and posters, and otherwise take part in the conference. As always, staff members spent some time meeting with community members at UCAR's exhibit hall booth. The following are some of the conference highlights from the perspective of NSF Unidata staff.
[Read More]14 February 2024
The Federation of Earth Science Information Partners (ESIP) is an open networked community that brings together science, data and information technology practitioners around Earth science issues.
The Raskin Scholarship is open to current graduate students in Earth or computer sciences who has an interest in community evolution of Earth Science data systems. Preference is given to applicants who can demonstrate a connection to ESIP-related activities.
[Read More]
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