UMN - Recommender Systems: Evaluation and Metrics
- Offered byCoursera
Recommender Systems: Evaluation and Metrics at Coursera Overview
Duration | 7 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Recommender Systems: Evaluation and Metrics at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 5 in the Recommender Systems Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Approx. 7 hours to complete
- English Subtitles: French, Portuguese (European), Russian, English, Spanish
Recommender Systems: Evaluation and Metrics at Coursera Course details
- 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.
Recommender Systems: Evaluation and Metrics at Coursera Curriculum
Preface
Introduction to Evaluation and Metrics
The Goals of Evaluation
Hidden Data Evaluation
Prediction Accuracy Metrics
Decision Support Metrics
Rank-Aware Top-N Metrics
Assignment Intro Video
Metric Computation Assignment Instructions
Basic Prediction and Recommendation Metrics Assignment
Advanced Metrics and Offline Evaluation
Beyond Basic Evaluation
Additional Item and List-Based Metrics
Experimental Protocols
Unary Data Evaluation
Temporal Evaluation of Recommenders (Interview with Neal Lathia)
Programming Assignment Introduction
Evaluating Recommenders
Offline Evaluation and Metrics Quiz
Programming Assignment Quiz
Online Evaluation
Introduction to Online Evaluation and User Studies
Usage Logs and Analysis
A/B Studies (Field Experiments)
User-Centered Evaluation (Interview with Bart Knijnenburg)
Online Evaluation Quiz
Evaluation Design
Matching Evaluation to the Problem/Challenge
Case Examples
Assignment Intro Video
Intro to Assignment: Evaluation Design Cases
Quiz Debrief
Assignment: Evaluation Design Cases
Recommender Systems: Evaluation and Metrics at Coursera Admission Process
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