Developed by Chao Shi, Sam O'Mullane, Sean Kickham, Reza Rad and Andrew Rubino Watch the project presentation: https://youtu.be/gkKGnnBenyk This project was completed by students from NYC Data Science Academy's 12-Week Bootcamp. Learn more about the bootcamp: http://nycdatascience.com/data-science-bootcamp/ People make decisions on where to eat based on friends’ recommendations. Since they know you, their suggestions matter more than those of strangers. For the capstone project, we built a hybrid Yelp recommendation system that can provide individualized recommendations based on your friend’s reviews on the social network. We built the machine learning models using Spark, and set up a Flask-Kafka-RDS-Databricks pipeline that allows a continuous stream of user requests. During the presentation, we will talk about the development framework and technical implementation of the pipeline. Read on their project posts and code: https://blog.nycdatascience.com/student-works/capstone/yelp-recommender-part-1/ https://blog.nycdatascience.com/student-works/yelp-recommender-part-2/