: Recommender systems are found in many ecommerce applications today. Recommender systems usually provide the user with a
list of recommendations that they might prefer, or supply predictions on how much the user might prefer each item. Choosing what book to
read next has always been a question for many. Even for students, deciding which textbook or reference book to read on a topic unknown to
them is a big question. There are two common approaches for providing recommendations, they are collaborative filtering and content
based filtering. In this report we try to present a model for a personalized recommendation system for books that uses hybrid
recommendation approach which is combination of content based and collaborative filtering. The proposed recommendation system tries to
learn the user’s preferences and recommends the books to the user based on their preferences. The system also recommends the books to
the user based on the user’s demographic parameters like age and location. The system also tries to understand the user’s favourite author
and recommends accordingly.