TFX: Production ML pipelines with TensorFlow

Robert Crowe (Google), Charles Chen (Google)

11:00am–11:40am Thursday, October 31, 2019

Location: Great American Ballroom J/K

Core technologies

Average rating:

(3.50, 2 ratings)

Who is this presentation for?

Data scientists, ML engineers, researchers, and ML ops and DevOps practitioners

Level

Intermediate

Description

ML development often focuses on metrics, delaying work on deployment and scaling issues. ML development designed for production deployments typically follows a pipeline model with scaling and maintainability as inherent parts of the design. Robert Crowe takes a deep dive into TensorFlow Extended (TFX), the open source version of the ML infrastructure platform that Google has developed for its own production ML pipelines.

Prerequisite knowledge

Experience with ML development and software development

What you'll learn

Discover issues and best practices for putting machine learning models and applications into production

Robert Crowe

Google

Robert Crowe is a data scientist and TensorFlow Developer Advocate at Google with a passion for helping developers quickly learn what they need to be productive. He’s used TensorFlow since the very early days and is excited about how it’s evolving quickly to become even better than it already is. Previously, Robert deployed production ML applications and led software engineering teams for large and small companies, always focusing on clean, elegant solutions to well-defined needs. In his spare time, Robert sails, surfs occasionally, and raises a family.

Website

Charles Chen

Google

Charles Chen is a senior software engineer at Google on the Tensorflow Extended (TFX) team. He previously worked on Google Cloud Dataflow and Apache Beam. Prior to Google, he earned his bachelor’s and master’s degrees in Computer Science from Stanford University.