Big Data and Machine Learning: Building a Recommendation Engine

In the previous blog on machine learning, we learnt about applying machine learning techniques to recommendation engines and an overview of collaborative filtering (CF) algorithms implemented in Apache Mahout. In this post, we'll discuss how to build a recommendation engine using Mahout. Let us take an example of a movie rating application that allows users to rate movies and suggests other movies that they might like. Following could be a data set where some users have rated some movies on a scale of 1 to 5 (highest). The empty cells denote that the user has not rated the movie.