Recommender Systems

This repository is for study recommender systems.
[ 추천시스템을 공부하기 위한 repository입니다. ]

I'm going to started with summarizing what I learned from 'Building Recommender Systems with Machine Learning and AI' course in LinkedIn, so I can refer to it later when I'm building my own recommender system.
[ 추천시스템을 만들때 참고하기 위해 LinkedIn의 'Building Recommender Systems with Machine Learning and AI' 코스를 통해 공부한 내용 및 코드를 요약하면서 시작합니다. ]

Index

• 1. Getting Started
• 2. Introduction to Python
• 3. Evaluating Recommender Systems
• [4. A Recommender Engine Framework]
• [5. Content-Based Filtering]
• [6. Neighborhood-Based Collaborative Filtering]
• [7. Matrix Factorization Methods]
• [8. Introduction to Deep Learning]
• [9. Deep Learning for Recommender Systems]
• [10. Scaling It Up]
• [11. Real-World Challenges of Recommender Systems]
• [12. Case Studies]
• [13. Hybrid Approaches]
• [14. Conclusion]