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Monday, May 20 • 4:20pm - 4:40pm
Continuous Training for Production ML in the TensorFlow Extended (TFX) Platform

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Large organizations rely increasingly on continuous ML pipelines in order to keep machine-learned models continuously up-to-date with respect to data. In this scenario, disruptions in the pipeline can increase model staleness and thus degrade the quality of downstream services supported by these models. In this paper we describe the operation of continuous pipelines in the Tensorflow Extended (TFX) platform that we developed and deployed at Google. We present the main mechanisms in TFX to support this type of pipelines in production and the lessons learned from the deployment of the platform internally at Google.

Speakers
DB

Denis Baylor

Google Research
KH

Kevin Haas

Google Research
SL

Sammy Leong

Google Research
RL

Rose Liu

Google Research
CM

Clemens Menwald

Google Research
HM

Hui Miao

Google Research
NP

Neoklis Polyzotis

Google Research
MT

Mitchell Trott

Google Research
MZ

Martin Zinkevich

Google Research


Monday May 20, 2019 4:20pm - 4:40pm
Stevens Creek Room

Attendees (11)