January 2018
Intermediate to advanced
310 pages
7h 48m
English
Content preview from Deep Learning for Computer Vision
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Deployment
In this chapter, we will learn how to deploy the trained model in the various platforms for maximum throughput and minimum latency. We will understand performance on various hardware such as a GPU and a CPU. We will follow the steps of deploying TensorFlow in platforms such as Amazon Web Services, Google Cloud Platform, and mobile platforms such as Android, iOS, and Tegra.
We will cover the following topics in this chapter:
- Understanding the factors affecting the performance of the deep learning model training and inference
- Improving the performance through various methods
- Seeing the benchmarks of various hardware and learning the steps to tweak them for maximum performance
- Using various cloud platforms for deployment
- Using various ...
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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.