關於此課程：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.
製作方： 明尼苏达大学
教學方： Michael D. Ekstrand, Assistant Professor
Dept. of Computer Science, Boise State University教學方： Joseph A Konstan, Distinguished McKnight Professor and Distinguished University Teaching Professor
Computer Science and Engineering
| 基本信息 | 課程 3（共 5 門，Recommender Systems Specialization ） |
| 語言 | 英語（English） |
| 如何通過 | 通過所有計分作業以完成課程。 |
| 用戶評分 |
授課大綱
第 1 週
Preface
2 個視頻
- 視頻: The Goals of Evaluation
Basic Prediction and Recommendation Metrics
5 個視頻, 1 個閱讀材料
- 視頻: Prediction Accuracy Metrics
- 視頻: Decision Support Metrics
- 視頻: Rank-Aware Top-N Metrics
- 視頻: Assignment Intro Video
- Reading: Metric Computation Assignment Instructions
已評分: Basic Prediction and Recommendation Metrics Assignment
第 2 週
Advanced Metrics and Offline Evaluation
6 個視頻, 1 個閱讀材料
- 視頻: Additional Item and List-Based Metrics
- 視頻: Experimental Protocols
- 視頻: Unary Data Evaluation
- 視頻: Temporal Evaluation of Recommenders (Interview with Neal Lathia)
- 視頻: Programming Assignment Introduction
- Reading: Evaluating Recommenders
已評分: Offline Evaluation and Metrics Quiz
已評分: Programming Assignment Quiz
第 3 週
Online Evaluation
4 個視頻
- 視頻: Usage Logs and Analysis
- 視頻: A/B Studies (Field Experiments)
- 視頻: User-Centered Evaluation (Interview with Bart Knijnenburg)
已評分: Online Evaluation Quiz
第 4 週
Evaluation Design
3 個視頻, 2 個閱讀材料
- 視頻: Case Examples
- 視頻: Assignment Intro Video
- Reading: Intro to Assignment: Evaluation Design Cases
- Reading: Quiz Debrief
已評分: Assignment: Evaluation Design Cases
常見問題解答
運作方式
Coursework
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製作方
明尼苏达大学
The University of Minnesota is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.
價格
| 購買課程 | |
|---|---|
| 訪問課程材料 | 可用 |
| 訪問評分的材料 | 可用 |
| 收到最終成績 | 可用 |
| 獲得可共享的課程證書 | 可用 |
評分和審閱
I was working on a cross-domain recommendation system where i would recommend books to a user whose movie ratings have been given. I made the algorithm but didn't have any idea as to how to evaluate it but this course helped me through. Thanks
the part of offline evaluation is really good and practical as well. However, although knowing online evaluation is a more complex subject, I felt it lacked a little bit how to put all this knowledge in practice.
It is not perfect but best of specialisation so far. It is a little bit philosophical rather than technical and formal, but it was exactly meet my current personal needs. Can not be recommended as a first and only introduction to a topic of an evaluation and metrics of recommender systems.
P.S. Exercises and quizzes, both main and honour, are somewhat eccentric.
not an easy course, specifically the honors track. the information is good, but not presented as well as in the previous two courses. Also there are errors in the honors assignment that make it unnecessarily difficult and you spend a lot of time on irrelevant things.