This repository is a review of the book 'Personalized Recommendation system with Python' written by Il Lim. This book deals with the operation principles of Collaborative Filtering (CF), Matrix Factorization (MF), and Deep Learning (DL) algorithms, which are currently most widely used as recommendation algorithms. The main objective is the establishment of personalized recommendation systems using Python. All of the practice codes are implemented through Google colab.
The overall architecture of the reposit is shown below.
| chapter | about |
|---|---|
| 1 | Introduction to recommendation system |
| 2 | Basic recommendation system |
| 3 | Collaborative Filtering |
| 4 | Matrix Factorization |
| 5 | Surprise package |
| 6 | Deep learning |
| 7 | Hybrid recommendation system |
| 8 | Sparse matrix |
| 9 | Issues with recommendation system |