Coursera MOOC / Non-credit 0

Recommender Systems

Name: Recommender Systems
Price: 49 USD
Availability: InStock

University of Minnesota

About this course

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.

90/100

CourseAsk score

What the provider tells you: 39/45
Who stands behind it: 35/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

understand the fundamental techniques of recommender systems
implement collaborative filtering methods
evaluate the effectiveness of different recommender models
apply matrix factorization and hybrid machine learning methods

Course objectives

equip learners with the skills to build and assess recommender systems
provide practical experience through exercises and projects

Machine Learning #machine learning #dimensionality reduction #data mining #recommender systems #collaborative filtering #algorithm evaluation #matrix factorization #user preferences #content-based recommendations #LensKit

$49.00

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