Recommender Systems: Evaluation and Metrics

4.36

Updated on

Course overview

Provider
Coursera
Course type
Free online course
Level
Mixed
Deadline
Flexible
Duration
7 hours
Certificate
Paid Certificate Available
Course author
Michael D. Ekstrand

Description

In this course you will learn how to evaluate recommender systems. You will gain familiarity with several families of metrics, including ones to measure prediction accuracy, rank accuracy, decision-support, and other factors such as diversity, product coverage, and serendipity. You will learn how different metrics relate to different user goals and business goals. You will also learn how to rigorously conduct offline evaluations (i.e., how to prepare and sample data, and how to aggregate results). And you will learn about online (experimental) evaluation. At the completion of this course you will have the tools you need to compare different recommender system alternatives for a wide variety of uses.

Similar courses

Machine Learning
  • Flexible deadline
  • 61 hours
  • Certificate
Neural Networks and Deep Learning
  • Flexible deadline
  • 27 hours
  • Certificate
Introduction to Machine Learning in Production
  • Flexible deadline
  • 10 hours
  • Certificate
Recommender Systems:  Evaluation and Metrics
  • English language

  • Recommended provider

  • Certificate available