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University of Minnesota

Recommender Systems

University of Minnesota via Coursera Specialization


A Recommender System is a process 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. The courses offer interactive, spreadsheet-based exercises to master different algorithms, along with an honors track where you can go into greater depth using the LensKit open source toolkit. By the end of this Specialization, you’ll be able to implement as well as evaluate recommender systems. The Capstone Project brings together the course material with a realistic recommender design and analysis project.


Course 1: Introduction to Recommender Systems: Non-Personalized and Content-Based
- Offered by University of Minnesota. This course, which is designed to serve as the first course in the Recommender Systems specialization, ... Enroll for free.

Course 2: Nearest Neighbor Collaborative Filtering
- Offered by University of Minnesota. In this course, you will learn the fundamental techniques for making personalized recommendations ... Enroll for free.

Course 3: Recommender Systems: Evaluation and Metrics
- Offered by University of Minnesota. In this course you will learn how to evaluate recommender systems. You will gain familiarity with ... Enroll for free.

Course 4: Matrix Factorization and Advanced Techniques
- Offered by University of Minnesota. In this course you will learn a variety of matrix factorization and hybrid machine learning techniques ... Enroll for free.

Course 5: Recommender Systems Capstone
- Offered by University of Minnesota. This capstone project course for the Recommender Systems Specialization brings together everything ... Enroll for free.


Taught by

Joseph A Konstan and Michael D. Ekstrand


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