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Python Deep Learning

You're reading from   Python Deep Learning Next generation techniques to revolutionize computer vision, AI, speech and data analysis

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781786464453
Length 406 pages
Edition 1st Edition
Languages
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Authors (4):
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Peter Roelants Peter Roelants
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Peter Roelants
Daniel Slater Daniel Slater
Author Profile Icon Daniel Slater
Daniel Slater
Valentino Zocca Valentino Zocca
Author Profile Icon Valentino Zocca
Valentino Zocca
Gianmario Spacagna Gianmario Spacagna
Author Profile Icon Gianmario Spacagna
Gianmario Spacagna
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Toc

Table of Contents (12) Chapters Close

Preface 1. Machine Learning – An Introduction FREE CHAPTER 2. Neural Networks 3. Deep Learning Fundamentals 4. Unsupervised Feature Learning 5. Image Recognition 6. Recurrent Neural Networks and Language Models 7. Deep Learning for Board Games 8. Deep Learning for Computer Games 9. Anomaly Detection 10. Building a Production-Ready Intrusion Detection System Index

Real-world applications of anomaly detection


Anomalies can happen in any system. Technically, you can always find a never-seen-before event that could not be found in the system's historical data. The implications of detecting those observations in some contexts can have a great impact (positive and negative).

In the field of law enforcement, anomaly detection could be used to reveal criminal activities (supposing you are in an area where the average person is honest enough to identify criminals standing out of the distribution).

In a network system, anomaly detection can help at finding external intrusions or suspicious activities of users, for instance, an employee who is accidentally or intentionally leaking large amounts of data outside the company intranet. Or maybe a hacker opening connections on non-common ports and/or protocols. In the specific case of Internet security, anomaly detection could be used for stopping new malware from spreading out by simply looking at spikes of visitors...

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