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R Deep Learning Projects

You're reading from   R Deep Learning Projects Master the techniques to design and develop neural network models in R

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788478403
Length 258 pages
Edition 1st Edition
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Authors (2):
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Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
Pablo Maldonado Pablo Maldonado
Author Profile Icon Pablo Maldonado
Pablo Maldonado
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Toc

What is so exciting about recurrent neural networks?

Coming from a mathematics background, in my rather hectic career I have seen many different trends, particularly during the last few years, which all sound very similar to me: "you have a problem? wavelets can save you!", "finite elements are the solution to everything", and similar over-enthusiastic claims. 

Of course, each tool has its time and place and, more importantly, an application domain where it excels. I find recurrent neural networks quite interesting for the many features they can achieve:

  • Produce consistent markup text (opening and closing tags, recognizing timestamp-like data)
  • Write Wikipedia articles with references, and create URLs from non-existing addresses, by learning what a URL should look like
  • Create credible-looking scientific papers from LaTeX

All these amazing features are...

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