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Deep Learning Techniques for IoT Security and Privacy (Hardcover, 1st ed. 2022) Loot Price: R4,262
Discovery Miles 42 620
Repayment Terms: R399 pm x 12*
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Deep Learning Techniques for IoT Security and Privacy (Hardcover, 1st ed. 2022): Mohamed Abdel-Basset, Nour Moustafa, Hossam...

Deep Learning Techniques for IoT Security and Privacy (Hardcover, 1st ed. 2022)

Mohamed Abdel-Basset, Nour Moustafa, Hossam Hawash, Weiping Ding

Series: Studies in Computational Intelligence, 997

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Loot Price R4,262 Discovery Miles 42 620 | Repayment Terms: R399 pm x 12*

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This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Studies in Computational Intelligence, 997
Release date: December 2021
First published: 2022
Authors: Mohamed Abdel-Basset • Nour Moustafa • Hossam Hawash • Weiping Ding
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 257
Edition: 1st ed. 2022
ISBN-13: 978-3-03-089024-7
Categories: Books > Computing & IT > Applications of computing > Databases > General
Books > Computing & IT > Applications of computing > Artificial intelligence > General
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LSN: 3-03-089024-4
Barcode: 9783030890247

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