Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud

© Manuel Amunategui, Mehdi Roopaei 2018

Manuel Amunategui and Mehdi RoopaeiMonetizing Machine Learninghttps://doi.org/10.1007/978-1-4842-3873-8_10

10. Recommending with Singular Value Decomposition on GCP

Manuel Amunategui¹  and Mehdi Roopaei²

(1)

Portland, Oregon, USA

(2)

Platteville, Wisconsin, USA

 

What to watch next? Let’s recommend movie options using SVD and the Wikipedia API on Google Cloud.

In this chapter, we’re going to build a movie recommender web application (Figure 10-1) using the MovieLens datasets containing, “100,000 ratings and 1,300 tag applications applied to 9,000 movies by 700 users.”¹ We will explore different similarity-measurement techniques and design a recommender application using singular value decomposition (SVD) and collaborative ...