This system is designed to help you discover captivating reads based on their popularity among avid readers. To create this recommendation engine, I handpicked the top 50 books with the highest average ratings, considering only those that received a minimum of 250 ratings. By utilizing this selection criteria, I aimed to provide you with a curated list of books that have resonated with a significant number of readers.

Collaborative recommendation systems are like a book club on steroids. Instead of relying on an algorithm to analyze the content of books, this system taps into the collective wisdom of readers. For my recommendation engine, I cherry-picked users who have generously shared their opinions by providing over 200 ratings. I also took into account books that have received at least 50 ratings, ensuring a diverse and engaging selection. By harnessing the power of collaboration, this system aims to connect you with books that align with your unique reading preferences. So, get ready to embark on a literary journey with recommendations straight from the minds of fellow book enthusiasts.

https://www.kaggle.com/datasets/arashnic/book-recommendation-dataset