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When analyzing data, sometimes the relationships between the data elements are important along with the scope of the question being asked. In those cases, it is better to represent the data as a graph and apply graph analytics. An example coming out of the COVID pand... Post by Don Acosta
RAPIDS’ 23.06 release is now available! This release adds a number of features and improvements we are excited about, including: Get started with the quick start installation instructions for conda, pip, or docker or read on to see more details on this months’ upgrad... Post by Alex Ravenel
cuSpatial continues barreling towards complete spatial relationship predicate (DE-9IM) support and Cartesian distance between any two geometries. In support of these goals cuSpatial 23.04 includes multiple new features, as well as a new notebook that shows off the ca... Post by Alex Ravenel
Introduction Graph Neural Networks (GNNs) are one of the fastest-growing tools in machine learning. GNNs combine a rich array of feature data (similar to the input of a traditional neural network) with network structure (represented as a graph). Depending on the work... Post by Alex Barghi
RAPIDS 23.04 is out! We are excited about this release, which includes major updates to cuSpatial, continued improvements to graph neural network functionality in our graph libraries, some performance improvements (and benchmarking!) in cuDF, and a number of improvem... Post by Alex Ravenel
First Release of the Year RAPIDS Release 23.02 is live. We are most excited to highlight several quality-of-life improvements. We have a new web presence for RAPIDS; we believe this will make learning, using, and adding to RAPIDS easier and more enjoyable than ever b... Post by Paul Mahler
