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https://github.com/matte34/amazon-recommendation-system

Item-to-item based recommendation system project using Amazon product data, combining matrix factorization (SVD) and collaborative filtering to predict user ratings and generate top recommendations. To evaluate and optimize the model's accuracy, the following performance metrics were explored: MAE, RMSE, precision, recall, F-measure, and NDCG.
https://github.com/matte34/amazon-recommendation-system

collaborative-filtering jupyter-notebook matrix-factorization python3 singular-value-decomposition sklearn

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Item-to-item based recommendation system project using Amazon product data, combining matrix factorization (SVD) and collaborative filtering to predict user ratings and generate top recommendations. To evaluate and optimize the model's accuracy, the following performance metrics were explored: MAE, RMSE, precision, recall, F-measure, and NDCG.

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# Amazon Recommendation System

Item-to-item based recommendation system project using Amazon product data, combining matrix factorization (SVD) and collaborative filtering to predict user ratings and generate top recommendations. To evaluate and optimize the model's accuracy, the following performance metrics were explored: MAE, RMSE, precision, recall, F-measure, and NDCG.

## What's included?

### Source Code:
- *Industrial_and_Scientific_5.json*
- *final_project.ipynb*
### Documents:
- *Data Science Project Report.pdf*
- *Data Science Project Slides.pdf*