Michael D. Ekstrand is an assistant professor in the Department of Computer Science at Boise State University. His research focuses on how to evaluate and understand recommender systems in terms of user goals and information needs, as well as how to support reproducible recommender systems research. He is the lead developer of LensKit, an open-source toolkit for building, researching, and studying recommender systems.
Coursera
Dive into the world of personalized recommendations with our 'Introduction to Recommender Systems' course. Explore non-personalized and content-based filtering methods, essential for creating effective recommendation systems that improve user experiences across various platforms.
Coursera
Dive into the world of personalized recommendation systems with our Nearest Neighbor Collaborative Filtering course. Master the fundamentals of making customized suggestions by understanding how algorithms identify and combine ratings from users with similar preferences. Perfect for data enthusiasts and professionals aiming to enhance user experience through targeted recommendations.
EdX
Explore the world of recommender systems and discover how they power personalized item suggestions on platforms like Netflix, Amazon, and LinkedIn. This course will teach you the fundamental concepts and methods used in creating relevant recommendations for users across various online ecosystems.