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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

RNN using Keras

In this section, we introduce an example using Keras. Keras is possibly the highest-level API for deep learning (again, at the time of writing, in this rapidly changing world of deep learning). This is very useful when you need to do production-ready models quite quickly, but is unfortunately sometimes not that great for learning, as everything is hidden away from you. Since, ideally, by the time you reach this section, an expert in recurrent neural networks, we can present you how to create a similar model. 

Before that, let's introduce a simple benchmark model. Something that comes to mind when we speak about the memory of a neural network is the following, well, what if I had sufficient storage to calculate the conditional probabilities and simulate text generation as a Markov process, where the state variable is the observed text? We will implement...

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