Recommender Systems Specialization – Your gateway to new career and income opportunities

Software Developers and Engineers, Recommender Systems are processes that seeks to predict user preferences. This Specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative filtering techniques, as well as advanced topics like matrix factorization, hybrid machine learning methods for recommender systems, and dimension reduction techniques for the user-product preference space. This Specialization is designed to serve both the data mining expert who would want to implement techniques like collaborative filtering in their job, as well as the data literate marketing professional, who would want to gain more familiarity with these topics. You will be equipped with high-demand and marketable skills in: Collaborative Filtering, Recommender Systems, Evaluation, LensKit Matrix and Factorization The five courses which comprise this Specialization include: 1) Introduction to Recommender Systems: Non-Personalized and Content-Based, 2) Nearest Neighbor Collaborative Filtering, 3) Recommender Systems: Evaluation and Metrics, 4) Matrix Factorization and Advanced Techniques, and 5) Recommender Systems Capstone Project. Much career success, Lawrence Wilson - Online Learning Central

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