Ecological Applications is concerned broadly with the applications of ecological science to environmental problems. It publishes papers that develop scientific principles to support environmental ...
This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...
A collaboration including the University of Oxford, University of British Columbia, Intel, New York University, CERN, and the National Energy Research Scientific Computing Center is working to make it ...
Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...
To fulfill the 2 Core Courses, take two Core Courses from two different Core Areas. Computational Data Science (CDS) Core Courses are classified into five areas: Data Analytics and Visualization, Data ...