Moviefy is an end-to-end Machine Learning project. It is similar to IMDb along with a crisp of machine learning to recommend you movies based on your search history. Simply put a Recommendation System is a filtration program whose prime goal is to predict the “rating” or “preference” of a user towards a domain-specific item. In our case, this domain-specific item is a movie. There are different filtration strategies but in this project I have used Item-based Collaborative Filtering

Recommendation systems are one of the widely used applications of Data Science in most companies based on products and online services. As a beginner, it is important to get a good grasp on how to implement such recommendation systems. By building this project, it will help me in understanding how this systems work and boost my skills.

Movielens dataset

The Movie Database