Long Short-Term Memory
Networks With Python
Develop Sequence Prediction
Models With Deep Learning
Jason Brownlee
i
Disclaimer
The information contained within this eBook is strictly for educational purposes. If you wish to apply
ideas contained in this eBook, you are taking full responsibility for your actions.
The author has made every e↵ort to ensure the accuracy of the information within this book was
correct at time of publication. The author does not assume and hereby disclaims any liability to any
party for any loss, damage, or disruption caused by errors or omissions, whether such errors or
omissions result from accident, negligence, or any other cause.
No part of this eBook may be reproduced or transmitted in any form or by any means, electronic or
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Copyright
Long Short-Term Memory Networks With Python
Copyright 2017 Jason Brownlee. All Rights Reserved.
Edition: v1.0
Contents
Copyright i
Contents ii
Preface iii
I Introductions iv
Welcome v
Who Is This Book For?................................... v
About Your Outcomes................................... vi
How to Read This Book.................................. vi
About the Book Structure................................. vi
About Lessons....................................... viii
About LSTM Models.................................... ix
About Prediction Problems................................ ix
About Python Code Examples............................... x
About Further Reading................................... xi
About Getting Help.................................... xii
Summary.......................................... xii
II Foundations 1
1 What are LSTMs 2
1.1 Sequence Prediction Problems............................ 3
1.2 Limitations of Multilayer Perceptrons........................ 7
1.3 Promise of Recurrent Neural Networks....................... 9
1.4 The Long Short-Term Memory Network
Long Short-Term Memory Networks With Python_Jason Brownlee.pdf