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Summary: There are five basic styles of recommenders differentiated mostly by their core algorithms. You need to understand what’s going on inside the box in order to know if you’re truly optimizing this critical tool.
Summary: In this multi-part series we walk through the full landscape of Recommenders. In this article we cover business considerations as well as issues for Recommenders as a group. In the next articles we’ll discuss the details of the five major types of recommenders, improving their performance, and finally the coming impact of deep learning on Recommenders.
Summary: As deep learning expands those capabilities are finding their way into the not-for-profit community in the service of conserving the earth’s wildlife and forests.
The for-profit world may be driving AI but it’s a solution to many problems in the not-for-profit…Continue
Summary: A great story about an AI-powered massive on-line open learning platform focused on STEM education. The platform and its content is to be available across many languages to serve students anywhere in preparing for a better life in STEM careers.