Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
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Applying deep learning at Google for recommendations

Ron Bodkin (Google)
11:50am12:30pm Wednesday, March 27, 2019
Average rating: ****.
(4.33, 6 ratings)

Who is this presentation for?

  • Data scientists, machine learning engineers, and their managers and executives



Prerequisite knowledge

  • Familiarity with machine learning, recommendation, and deep learning

What you'll learn

  • Learn the applications of embeddings, how feature engineering changes with deep learning, ranking by distance in vector space, objective functions for recommendation, and latent cross for handling contextual variables end-to-end ML requirements


Google uses deep learning extensively in new and existing products. Join Ron Bodkin to learn how Google has used deep learning for recommendations at YouTube, in the Play store, and for customers in Google Cloud. You’ll explore the role of embeddings, recurrent networks, contextual variables, and wide and deep learning and discover how to do candidate generation and ranking with deep learning. You’ll look at the features used, see how to think about contextual variables like recency of videos, understand the metrics used for evaluating recommendations and handling long tail distributions, and dive into TensorFlow Extended, which is used at Google for the end-to-end system that prepares, trains, and serves machine learning recommendations. Along the way, you’ll find out how customers are using some of the same capabilities in Google Cloud for recommendations.

Photo of Ron Bodkin

Ron Bodkin


Ron Bodkin is a technical director on the applied artificial intelligence team at Google, where he provides leadership for AI success for customers in Google’s Cloud CTO office. Ron engages deeply with Global F500 enterprises to unlock strategic value with AI, acts as executive sponsor with Google product and engineering to deliver value from AI solutions, and leads strategic initiatives working with customers and partners. Previously, Ron was the founding CEO of Think Big Analytics, a company that provides end-to-end support for enterprise big data, including data science, data engineering, advisory, and managed services and frameworks such as Kylo for enterprise data lakes. When Think Big was acquired by Teradata, Ron led global growth, the development of the Kylo open source data lake framework, and the company’s expansion to architecture consulting; he also created Teradata’s artificial intelligence incubator.