Machine learning for Recommender Systems Free English ‎(en)‎

  • Recruiting People1,000 people

  • Target ClassALL

  • Enrollment Period11-01-2022 ~ 12-31-2023

  • Learning period11-01-2022 ~ 12-31-2023

  • Payment StatusFree

  • Approval MethodAutomatic Approval

Log in to take courses.
Class Introduction

image

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.

image

 

image

- 김재광 성균관대학교 소프트웨어학과 교수 

 

 

image

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)

Preview Lecture Video
The preview video does not exist.
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
  • Colleges & Schools
    College of Computing and Informatics
  • Topics
    Engineering & Tech
Professor
Back to Previous Page