April 2020
Intermediate to advanced
330 pages
7h 44m
English
Content preview from Hands-On Deep Learning with R
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Summary
Having completed this chapter, you should now have all of the libraries that will be used in this book installed. In addition, you should be familiar with the syntax for each of them, and you should have seen a preliminary example of how to train a model using each one. We also explored some of the differences between the deep learning libraries, noting their strengths as well as their limitations. The three main packages (Keras, MXNet, and H2O) are widely used for deep learning in industry and academia, and an understanding of these will enable you to tackle a number of deep learning problems. We are now ready to explore them all in more depth. However, before we do, we will review neural networks—the building block for all deep ...
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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.