shahriar-rahman/A-Comparative-Analysis-of-Amazon-Book-Ratings-using-Collaborative-Filtering
Juxtaposing different Recommender Algorithms by utilizing the concept of Collaborative Filtering to analyze the Amazon Book Ratings.
This project helps e-commerce businesses or content platforms improve their product recommendation systems. By analyzing customer reviews and ratings for books, it takes in historical user feedback and generates a robust model to suggest items. E-commerce managers, product strategists, or anyone building an online store with many products and user reviews would find this useful.
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Use this if you need to understand how different collaborative filtering algorithms perform on large datasets of user ratings to provide better product suggestions.
Not ideal if your recommendation needs are based on item content or user demographics rather than solely on user-item interaction data like ratings.
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MIT
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Last pushed
Feb 06, 2024
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