STEPS: 1.Collected the ratings data for 200k+ books from multiple CSV files and merged them into a single data frame. DATASETS: URL:https://www.kaggle.com/datasets/arashnic/book-recommendation-dataset
2.Imputed missing values and performed EDA on the data to extract meaningful insights.
3.Implemented recommendation models based on **Popularity-based filtering and **Collaborative Filtering using Matrix Factorization, Item-Item similarity matrix and **Content-based Filtering techniques.