You're reading from Hands-On Neural Networks with Keras

Product typeBook

Published inMar 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781789536089

Edition1st Edition

Languages

Python

Tools

Keras

Concepts

Neural Networks

Author (1)

Niloy Purkait

Building a SimpleRNN

The SimpleRNN model in Keras is a basic RNN layer, like the ones we discussed earlier. While it has many parameters, most of them are set with excellent defaults that will get you by for many different use cases. Since we have initialized the RNN layer as the first layer of our model, we must pass it an input shape, corresponding to the length of each sequence (which we chose to be 40 characters earlier) and the number of unique characters in our dataset (which was 44). While this model is computationally compact to run, it gravely suffers from the vanishing gradients problem we spoke of. As a result, it has some trouble modeling long-term dependencies:

from keras.models import Sequential
from keras.layers import Dense, Bidirectional, Dropout
from keras.layers import SimpleRNN, GRU, BatchNormalization
from keras.optimizers import RMSprop
'''Fun...

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Hands-On Neural Networks with Keras

Published in: Mar 2019Publisher: PacktISBN-13: 9781789536089

Author (1)

Niloy Purkait

Niloy Purkait is a technology and strategy consultant by profession. He currently resides in the Netherlands, where he offers his consulting services to local and international companies alike. He specializes in integrated solutions involving artificial intelligence, and takes pride in navigating his clients through dynamic and disruptive business environments. He has a masters in Strategic Management from Tilburg University, and a full specialization in data science from Michigan University. He has advanced industry grade certifications from IBM, in subjects like signal processing, cloud computing, machine and deep learning. He is also perusing advanced academic degrees in several related fields, and is a self-proclaimed lifelong learner.
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Author (1)

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