December 2018
Intermediate to advanced
274 pages
7h 46m
English
Content preview from Machine Learning for Mobile
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TensorFlow Mobile in Android
In the previous chapter, we focused on supervised learning and unsupervised learning, and learned about the different types of learning algorithms. In this chapter, we will get introduced to TensorFlow for mobile, and go through a sample program implementation using TensorFlow for mobile. In Chapter 9, Neural Networks on Mobile, we will be using it to implement a classification algorithm. But we need to understand how TensorFlow for mobile works and be able to write samples using it before we can implement machine learning algorithms with it. The objective of this chapter is to get introduced to TensorFlow, TensorFlow Lite, TensorFlow for mobile, and their ways of working, and to try hands-on examples using
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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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.