Warehouse Stock Clearance Sale

Grab a bargain today!


Sign Up for Fishpond's Best Deals Delivered to You Every Day
Go
Applied Learning Algorithms ­for Intelligent Iot
By Pethuru Raj Chelliah (Edited by), Usha Sakthivel (Edited by), Susila Nagarajan (Edited by)

Rating
Format
Hardback, 356 pages
Other Formats Available

Paperback : HK$391.00

Published
United Kingdom, 1 October 2021

This book vividly illustrates all the promising and potential machine learning (ML) and deep learning (DL) algorithms through a host of real-world and real-time business use cases. Machines and devices can be empowered to self-learn and exhibit intelligent behavior. Also, Big Data combined with real-time and runtime data can lead to personalized, prognostic, predictive, and prescriptive insights. This book examines the following topics:

  • Cognitive machines and devices
  • Cyber physical systems (CPS)
  • The Internet of Things (IoT) and industrial use cases
  • Industry 4.0 for smarter manufacturing
  • Predictive and prescriptive insights for smarter systems
  • Machine vision and intelligence
  • Natural interfaces
  • K-means clustering algorithm
  • Support vector machine (SVM) algorithm
  • A priori algorithms
  • Linear and logistic regression

Applied Learning Algorithms for Intelligent IoT clearly articulates ML and DL algorithms that can be used to unearth predictive and prescriptive insights out of Big Data. Transforming raw data into information and relevant knowledge is gaining prominence with the availability of data processing and mining, analytics algorithms, platforms, frameworks, and other accelerators discussed in the book. Now, with the emergence of machine learning algorithms, the field of data analytics is bound to reach new heights.

This book will serve as a comprehensive guide for AI researchers, faculty members, and IT professionals. Every chapter will discuss one ML algorithm, its origin, challenges, and benefits, as well as a sample industry use case for explaining the algorithm in detail. The book’s detailed and deeper dive into ML and DL algorithms using a practical use case can foster innovative research.

Show more

Our Price
HK$800
Elsewhere
HK$1,106.43
Save HK$306.43 (28%)
Ships from Australia Estimated delivery date: 1st May - 9th May from Australia
Free Shipping Worldwide

Buy Together
+
Buy together with Applied Learning Algorithms for Intelligent IoT at a great price!
Buy Together
HK$1,191
Elsewhere Price
HK$1,262.59
You Save HK$71.59 (6%)

Product Description

This book vividly illustrates all the promising and potential machine learning (ML) and deep learning (DL) algorithms through a host of real-world and real-time business use cases. Machines and devices can be empowered to self-learn and exhibit intelligent behavior. Also, Big Data combined with real-time and runtime data can lead to personalized, prognostic, predictive, and prescriptive insights. This book examines the following topics:

Applied Learning Algorithms for Intelligent IoT clearly articulates ML and DL algorithms that can be used to unearth predictive and prescriptive insights out of Big Data. Transforming raw data into information and relevant knowledge is gaining prominence with the availability of data processing and mining, analytics algorithms, platforms, frameworks, and other accelerators discussed in the book. Now, with the emergence of machine learning algorithms, the field of data analytics is bound to reach new heights.

This book will serve as a comprehensive guide for AI researchers, faculty members, and IT professionals. Every chapter will discuss one ML algorithm, its origin, challenges, and benefits, as well as a sample industry use case for explaining the algorithm in detail. The book’s detailed and deeper dive into ML and DL algorithms using a practical use case can foster innovative research.

Show more
Product Details
EAN
9780367635947
ISBN
0367635941
Publisher
Other Information
170 Line drawings, black and white; 170 Illustrations, black and white
Dimensions
23.4 x 15.6 x 2.2 centimeters (0.74 kg)

Table of Contents

1. Convolutional Neural Network in Computer Vision. 2. Trends and Transition in the Machine Learning (ML) Space. 3. Deep Learning: Algorithms, Platforms, Applications, and Research Trends in IoT. 4. The Next-Generation IoT Use Cases across Industry Verticals using Machine and Deep Learning Algorithms. 5. A Panoramic View of Cyber Attack Detection and Prevention Using Machine Learning and Deep Learning Approaches. 6. Regression Algorithms in Machine Learning. 7. Machine Learning Based Industrial Internet of Things (IIoT) and Its Applications. 8. Employee Turnover Prediction Using Single Voting Model. 9. A Novel Implementation of Sentiment Analysis towards Data Science. 10. Conspectus of K-Means Clustering Algorithm. 11. Systematic Approach to Deal with Internal Fragmentation and Enhancing Memory Space during COVID-19. 12. IoT Automated Spy Drone to Detect and Alert Illegal Drug Plants for Law Enforcement. 13. Expounding K-Means-inspired Network Partitioning Algorithm for SDN Controller Placement . 14. An Intelligent Deep Learning Based Wireless Underground Sensor System for IoT Based Agricultural Application. 15. Predicting Effectiveness of Solar Pond Heat Exchanger with LTES Containing CUO Nanoparticle Using Machine Learning.

About the Author

Dr. Pethuru Raj is Chief Architect and Vice President of the Site Reliability Engineering (SRE) Division of Reliance JioInfocomm. Ltd., Bangalore, India.


Dr. Usha Sakthivel is the dean of research, Department of Computer Engineering, RajaRajeswari College of Engineering, Bangalore, India.


Dr. Susila N is a professor and head of the Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore, India.

Show more
Review this Product
Ask a Question About this Product More...
 
Item ships from and is sold by Fishpond Retail Limited.

Back to top