You're reading from Hands-On Reinforcement Learning with Python

Product typeBook

Published inJun 2018

Reading LevelIntermediate

PublisherPackt

ISBN-139781788836524

Edition1st Edition

Languages

Python

Tools

TensorFlow Keras

Concepts

Reinforcement Learning

Author (1)

Sudharsan Ravichandiran

RNN

The birds are flying in the ____. If I ask you to predict the blank, you might predict sky. How did you predict that the word sky would be a good fit to fill this blank? Because you read the whole sentence and predicted sky would be the right word based on understanding the context of the sentence. If we ask our normal neural network to predict the right word for this blank, it will not predict the correct word. This is because a normal neural network's output is based on only the current input. So, the input to the neural network will be just the previous word, the. That is, in normal neural networks, each input is independent of the others. So, it will not perform well in a case where we have to remember the sequence of input to predict the next sequence.

How do we make our network remember the whole sentence to predict the next word correctly? Here is where RNN comes...

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Hands-On Reinforcement Learning with Python

Published in: Jun 2018Publisher: PacktISBN-13: 9781788836524

Author (1)

Sudharsan Ravichandiran

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
Read more about Sudharsan Ravichandiran

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Author (1)

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