How many of you still like to watch old English movies? If yes, which one you want to start with? which suits to your interest? And many of us are uncertain which movies we may like to watch? Ever wondered you can have all the above issues addressed in one place, so here we come with the Recommendation Engine which gives you the best match for your movie interest.

So now the question is, what is the idea behind telling you the movies you like to watch from our app. We thought facebook would be the best place where we can get to know your interests. Our app exactly does the same, we will take the movies liked by you in your facebook profile and use them to recommend you the old english movies. So visit this link and get free recommendations.


How we do it?

Lets know the technical background of the whole magic of recommendation engine.


This is one of the apps which is completely based on Machine Learning. Recommendation engines are normally designed in two approaches

  • Collaborative Filtering : It is based on collecting and analyzing a large amount of information on users’ behaviors, activities or preferences and predicting what users will like based on their similarity to other users.

  • Content Based Filtering : It is based on a description of the item and a profile of the user’s preference . In a content-based recommender system, keywords are used to describe the items; beside, a user profile is built to indicate the type of item this user likes.

We have done the collaborative filtering method where our model is developed based on the ratings provided by the users for different movies.

Our Model

We used Alternating Least Squares (ALS) Matrix Factorization model. ALS Matrix Factorization Model is the well known algorithm for recommendations these days. It allows us to handle both implicit feedback and explicit feedback data from the users. It has the ability to build the feature set for the movies and the users who has rated them.

We also use K-Means clustering to cluster similar movies. Based on the feature set built by ALS model for the movies we cluster the movies. The clustering assists us to dynamically fetch the movies and deliver to the user at faster rate.

“So this is it, the whole idea behind the mysterious recommendation engine using the Machine Learning techniques using the superior models.”

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