Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Today we’re joined by JJ Espinoza, former Director of Data Science at 20th Century Fox.

In this talk we start out with a discussion on JJ’s transition from econometrician to data scientist, and then dig into his and his team’s experience building and deploying a content recommendation system from the ground up. In our conversation, we explore the design of a couple of key components of their system, the first of which processes movie scripts to make recommendations about which movies the studio should make, and the second processes trailers to determine which should be recommended to users. We discuss the challenges they’ve encountered fielding these systems, some of the tools that were used along the way, and a few of the upcoming projects that could be layered on top of the platform they’ve built.

About JJ

Mentioned in the Interview

“More On That Later” by Lee Rosevere licensed under CC By 4.0

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