Artificial intelligence trends for data analytics using machine learning and deep learning approaches

Author(s)

    • Gayathri Devi, K.
    • Rath, Mamata
    • Dieu, Nguyen Thi

Bibliographic Information

Artificial intelligence trends for data analytics using machine learning and deep learning approaches

edited by K. Gayathri Devi, Mamata Rath, and Nguyen Thi Dieu Linh

(Artificial intelligence (AI) : elementary to advanced practices / series editors, Vijender Kumar Solanki, Zhongyu (Joan) Lu, and Valentina E. Balas)

CRC Press, 2021

  • : hbk

Available at  / 2 libraries

Search this Book/Journal

Note

Includes bibliographical references and index

Description and Table of Contents

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

Table of Contents

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

by "Nielsen BookData"

Related Books: 1-1 of 1

Details

Page Top