This is a very good lecture.
I'm listening to it because I need a recommendation algorithm for an ongoing project,
and it's been very helpful.
There's one bad review saying the sound cuts out,
but the sound only goes silent briefly when the instructor pauses after speaking, and it doesn't cut out in the middle of speech to interfere with the lecture.

cwforest062365

This course covers everything from the basic concepts of recommendation systems to the principles of applying deep learning. Learn about various recommendation algorithms such as collaborative filtering, content-based filtering, and hybrid recommendation systems, and develop practical skills for developing recommendation services!

trimurti

2025 추석맞이 감사할인

AI-based recommendation system

Thank you for properly evaluating the value of the lecture. If there are any inconveniences during the lecture, please always let me know and I will fix them immediately. Thank you.

이론과 실습 한 번에

이론 실습 모두

본 강의는 추천시스템의 기본개념부터 딥러닝 적용원리까지 다룹니다. 협업 필터링, 콘텐츠 기반 필터링, 하이브리드 추천 시스템 등 다양한 추천 알고리즘을 배우며 추천 서비스 개발을 위한 실무역량을 키워보세요!

YoungJea Oh

입문

초급

중급이상

Deep Learning(DL)

딥러닝

Machine Learning(ML)

머신러닝

Recommendation System

파이썬

Python

텐서플로

Tensorflow

인공지능 활용 추천 시스템

교육 환경 준비

컨텐트 기반 필터링 (Content Based Filtering)

협업 필터링 (Collaborative Filtering)

지식 기반 필터링 (Knowlege-Based Filtering)

Deep Learning을 이용한 Matrix Factorization (MF) 기반 추천 시스템

하이브리드 모델 (Hybrid Model)