Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches
1st Edition
Published on 7. October 2020
266 pages
978-1-000-17953-8 (ISBN)
Description
Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems.
The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications.
Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems.
Features
Includes AI-based decision-making approaches
Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images
Covers automation of systems through machine learning and deep learning approaches and its implications to the real world
Presents data analytics and mining for decision-support applications
Offers case-based reasoning
The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications.
Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems.
Features
Includes AI-based decision-making approaches
Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images
Covers automation of systems through machine learning and deep learning approaches and its implications to the real world
Presents data analytics and mining for decision-support applications
Offers case-based reasoning
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
36 Tables, black and white; 54 Line drawings, black and white; 80 Halftones, black and white; 134 Illustrations, black and white
ISBN-13
978-1-000-17953-8 (9781000179538)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
K. Gayathri Devi | Mamata Rath | Nguyen Thi Dieu Linh
Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches
Book
10/2024
1st Edition
CRC Press
€80.70
Shipment within 15-20 days
K. Gayathri Devi | Mamata Rath | Nguyen Thi Dieu Linh
Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches
Book
10/2020
1st Edition
CRC Press
€231.00
Shipment within 15-20 days
Persons
K. Gayathri Devi has 20 years of experience as a professor in the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. She has published papers in national and international journals and conferences. She has published patents. She is the reviewer of many SCI and Scopus indexed journals. She has received many proficiency awards and grants, and is a topper in the NPTEL online certification examination. She is the life member of ISTE, International Association of Engineers and Institute of Research Engineers and Doctors. Her research interests include Medical Image Processing, Internet of Things, Artificial Intelligence, and Embedded Systems.
Mamata Rath has about 13 years of experience as an assistant professor. She has many research publications, including SCI, Scopus, dblp, and Web of Science indexing in different international journal and conferences. Her research interests include Information Systems, Wireless Networks, Internet of Things, Computer Security, Real Time Systems, Ubiquitous Computing, Big Data and Artificial Intelligence. Currently she is an assistant professor of Information Technology at Birla Global University, Odisha, India.
Nguyen Thi Dieu Linh has more than 18 years of academic experience in electronics, IoT, Telecommunication, Big Data, and Artificial Intelligence. She has published more than 15 research articles in national and international journals, books, and conference proceedings. She is reviewer for Information Technology Journal, Mobile Networks and Applications Journal, and some international conferences. Now she is a head of Department of Electronics and Telecommunication Engineering, Faculty of Electronics Engineering, Hanoi University of Industry (HaUI), Vietnam.
Mamata Rath has about 13 years of experience as an assistant professor. She has many research publications, including SCI, Scopus, dblp, and Web of Science indexing in different international journal and conferences. Her research interests include Information Systems, Wireless Networks, Internet of Things, Computer Security, Real Time Systems, Ubiquitous Computing, Big Data and Artificial Intelligence. Currently she is an assistant professor of Information Technology at Birla Global University, Odisha, India.
Nguyen Thi Dieu Linh has more than 18 years of academic experience in electronics, IoT, Telecommunication, Big Data, and Artificial Intelligence. She has published more than 15 research articles in national and international journals, books, and conference proceedings. She is reviewer for Information Technology Journal, Mobile Networks and Applications Journal, and some international conferences. Now she is a head of Department of Electronics and Telecommunication Engineering, Faculty of Electronics Engineering, Hanoi University of Industry (HaUI), Vietnam.
Content
1. An Artificial Intelligence System Based Power Estimation Method for CMOS VLSI Circuits 2. Awareness Alert and Information Analysis in Social Media Networking Using Usage Analysis and Negotiable Approach 3. Object Detection and Tracking in Video Using Deep Learning Techniques: A Review 4. Fuzzy MCDM: Application in Disease Risk and Prediction 5. Deep Learning Approach to Predict and Grade Glaucoma from Fundus Images through Constitutional Neural Networks 6. A Novel Method for Securing Cognitive Radio Communication Network Using the Machine Learning Schemes and a Rule Based Approaches 7. Detection of Retinopathy of Prematurity Using Convolution Neural Network 8. Impact of Technology on Human Resource Information System and Achieving Business Intelligence in Organizations 9. Proficient Prediction of Acute Lymphoblastic Leukemia Using Machine Learning Algorithm 10. Role of Machine Learning in Social Area Networks 11. Breast Cancer and Machine Learning: Interactive Breast Cancer Prediction Using Naive Bayes Algorithm 12. Deep Networks and Deep Learning Algorithms 13. Machine Learning for Big Data Analytics, Interactive and Reinforcement 14. Fish Farm Monitoring System Using IoT and Machine Learning
