November 2020
Intermediate to advanced
314 pages
5h 55m
English
Content preview from Learn TensorFlow Enterprise
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Chapter 9: Serving a TensorFlow Model
By now, after learning all the previous chapters, you have seen many facets of a model building process in TensorFlow Enterprise (TFE). Now it is time to wrap up what we have done and look at how we can serve the model we have built. In this chapter, we are going to look at the fundamentals of serving a TensorFlow model, which is through a RESTful API in localhost. The easiest way to get started is by using TensorFlow Serving (TFS). Out of the box, TFS is a system for serving machine learning models built with TensorFlow. Although it is not yet officially supported by TFE, you will see that it works with models built by TFE 2. It can run as either a server or as a Docker container. For our ease, we are ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.