April 2017
Intermediate to advanced
320 pages
7h 46m
English
Content preview from Deep Learning with TensorFlow
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Summary
GPUs are specialized hardware components that were originally developed for graphics applications. However, it was realized that GPUs could be used to perform computations in a DNN architecture.
In the second part of this chapter, we saw how to install a GPU-enabled TensorFlow and how to manage GPU devices.
In the next chapter, we will discuss some advanced programming features using TensorFlow by integrating with other third-party tools such as, Keras, PrettyTensor and TFLearn. In addition, we’ll give an overview of some TensorFlow-based framework--Keras, PrettyTensor and TFLearn.
We'll show the main topics of these frameworks, with very interesting application examples.
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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.