July 2020 · with Hannes Hapke
Building Machine Learning Pipelines
Automating Model Life Cycles with TensorFlow
This book is a comprehensive guide to deploying machine learning models to production using TensorFlow Extended (TFX). We encourage the standardization of ML model deployment - at the time of writing, this was mostly done with ad hoc code, and many models never made it to production. The technology has moved on, but the introduction in particular is still well worth reading if you want to set up repeatable processes for putting ML models into production.
From the book cover:
“Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively.
In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems.”