Machine learning-based recommendation systems have become very popular and necessary in recent years in a variety of applications, such as movies, music, books, news, search queries, and products. They have brought in a dramatic change in how people buy products and find information. Recommendation systems usually recommend products to users based on their tastes and preferences. Users typically find relevant products and information that they did not know existed or did not know how to ask for.
This chapter is designed for you to understand and create recommendation systems, and will cover the following topics:
Building recommendation systems
Building a recommendation system with MLlib
Building a recommendation system with Mahout and Spark