If you don’t like to read, you haven’t found the right book - J.K. Rowling
The goal of this project is creation of books recommendation system. I compared different models and collaborative filtering approaches to find the best solution.
This project is written in Python 3.8.3.
The requirements.txt file contains all required Python libraries. They can be installed using:
pip install -r requirements.txt
Goodbooks-10k - only books.csv and ratings.csv are used in this project.
The best RMSE and MAE were achieved by SVD - we want to minimalize these values. All models are better than random approach.
| Model | RMSE | MAE |
|---|---|---|
| Random | 1.321724 | 1.051821 |
| KNNBasic user_based | 0.951170 | 0.760192 |
| KNNBaseline user_based | 0.853463 | 0.671673 |
| KNNWithZScore user_based | 0.855638 | 0.665709 |
| KNNWithMeans user_based | 0.857791 | 0.668161 |
| KNNBasic item_based | 0.888497 | 0.696982 |
| KNNBaseline item_based | 0.856132 | 0.668380 |
| KNNWithZScore item_based | 0.866092 | 0.677739 |
| KNNWithMeans item_based | 0.864491 | 0.676945 |
| SVD | 0.845166 | 0.663349 |
