Machine Leaing Hybridization and Optimization for Intelligent Applications (Computational Intelligence Techniques)

by: Tanvir Habib Sardar (Editor),Bishwajeet Kumar Pandey (Editor)

Publisher: CRC Press

Edition: 1st

Publication Date: 2024/10/28

Language: English

Print Length: 338 pages

ISBN-10: 1032737530

ISBN-13: 9781032737539

Book Description

This book discusses state-of-the-art reviews of the existing machine leaing techniques and algorithms including hybridizations and optimizations. It covers applications of machine leaing via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, patte recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation.Features: • Focuses on hybridization and optimization of machine leaing techniques.• Reviews supervised, unsupervised, and reinforcement leaing using case study-based applications.• Covers the latest machine leaing applications in as diverse domains as the Inteet of Things, data science, cloud computing, and distributed and parallel computing.• Explains computing models using real-world examples and dataset-based experiments.• Includes case study-based explanations and usage for machine leaing technologies and applications.This book is aimed at graduate students and researchers in machine leaing, artificial intelligence, and electrical engineering.

About the Author

This book discusses state-of-the-art reviews of the existing machine leaing techniques and algorithms including hybridizations and optimizations. It covers applications of machine leaing via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, patte recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation.Features: • Focuses on hybridization and optimization of machine leaing techniques.• Reviews supervised, unsupervised, and reinforcement leaing using case study-based applications.• Covers the latest machine leaing applications in as diverse domains as the Inteet of Things, data science, cloud computing, and distributed and parallel computing.• Explains computing models using real-world examples and dataset-based experiments.• Includes case study-based explanations and usage for machine leaing technologies and applications.This book is aimed at graduate students and researchers in machine leaing, artificial intelligence, and electrical engineering.