Course details
Machine learning for Recommender Systems Free English (en)
Recruiting People1,000 people
Target ClassALL
Enrollment Period11-01-2022 ~ 03-06-2031
Learning period11-01-2022 ~ 03-05-2031
Payment StatusFree
Approval MethodAutomatic Approval
Class Introduction
In Course 3 of the Machine Learning for Recommender Systems Specialization, offered by Sungkyunkwan Univ., you will:
a) understand the data preprocessing of the raw data for recommender systems.
b) apply the recommender systems (content based filtering and collaborative filtering).
measure the performance of the methods for the recommender systems such as mAP, nDCG, and ED.understand the basic concepts of machine learning.
c) understand a typical memory-based method, the K nearest neighbor method.
- 김재광 성균관대학교 소프트웨어학과 교수
| 주 (Week) | 학습 내용 (Contents) |
| Week 1 | Introduction to Recommender Systems |
| Week 2 | Collaborative Filtering |
| Week 3 | Recommender System with Deep Learning |
| Week 4 | Further Understanding of Recommeder Systems |
문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
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Course Introduction
This specialization understands the machine learning algorithms needed to understand and implement recommender systems. To this end, the content of the class is conducted in the form of theory, quizzes, and assignments. This specialization consists of three modules:
Classification
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Colleges & SchoolsCollege of Computing and Informatics
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TopicsEngineering & Tech
Professor
