December 2018
Intermediate to advanced
274 pages
7h 46m
English
Content preview from Machine Learning for Mobile
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Summary
In this chapter, we got introduced to Google's machine learning tools for Mobile and looked at the various flavors of the toolkit – TensorFlow for Mobile and TensorFlow Lite. We also explored the architecture of a TensorFlow-ML-enabled mobile application. Then we discussed the architecture and details of TensorFlow Lite and its components, and even demonstrated a simple use case for an android mobile application using TensorFlow for mobile.
In the next chapter, we will be using the TensorFlow for mobile that we discussed here to implement a classification algorithm.
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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.