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Title TFX : Production ML pipelines with TensorFlow [electronic resource] / Crowe, Robert.
Imprint O'Reilly Media, Inc., 2020.


 Internet  Streaming Video    AVAILABLE
Edition 1st edition.
Description 1 online resource (1 video file, approximately 42 min.)
Note Available only to authorized UTEP users.
Performer Presenter, Robert Crowe, Charles Chen.
Reproduction Electronic reproduction. Boston, MA : Safari. Available via World Wide Web.
Note Mode of access: World Wide Web.
Copyright © O'Reilly Media, Inc.
Made available through: Safari, an O'Reilly Media Company.
Online resource; Title from title screen (viewed February 28, 2020)
Subject Machine learning.
Artificial intelligence.
Genre Electronic videos.
Summary 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 and Charles Chen (Google) 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.
Other Author Chen, Charles, author.
Safari, an O'Reilly Media Company.