Summary
In this chapter, we implemented two end-to-end projects to develop item-based collaborative filtering for movie similarity measurement and model-based recommendation with Spark. We also saw how to interoperate between ALS and MF and develop scalable movie recommendations engines. Finally, we saw how to deploy this model in production.
As human beings, we learn from past experiences. We haven't gotten so charming by accident. Years of positive compliments as well as criticism have all helped shape us into what we are today. You learn what makes people happy by interacting with friends, family, and even strangers, and you figure out how to ride a bike by trying out different muscle movements until it just clicks. When you perform actions, ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access