Advanced AI and Data Science Applications
1st Edition
Published on 24. September 2025
Book
Hardback
16 pages
978-1-032-89465-2 (ISBN)
Description
Advanced AI and Data Science Applications explores how the latest developments in artificial intelligence (AI) and data science are transforming diverse domains. The book blends theory and practice to serve as a roadmap to help readers understand how these cutting-edge technologies are revolutionizing practices across various fields. By providing a mix of theoretical insights and practical implementations, the book offers a holistic understanding of advanced AI and data science applications. Highlights of the book include:
Metaheuristic optimization techniques for solving complex AI model training challenges
The impact of AI and data science on urban development
Implementing AI for enhanced cybersecurity in industrial control systems
A comparative study of traditional and AI-based methods for English speech recognition
Temporal dependency modeling in real-time data streams using a deep learning model
Predictive analytics for financial fraud detection and risk management
Data science in manufacturing for cost reduction and efficiency
AI-driven agricultural analytics
Featuring such advanced modeling techniques as predictive modeling, simulation, and optimization algorithms, the book presents innovative solutions that emphasize benefits and practicality. With its emphasis on interdisciplinary applications, it showcases successful projects that underscore the synergy between AI and data science domains, empowering readers to harness the power of innovation for enhanced problem-solving and efficiency in interdisciplinary realms.
Metaheuristic optimization techniques for solving complex AI model training challenges
The impact of AI and data science on urban development
Implementing AI for enhanced cybersecurity in industrial control systems
A comparative study of traditional and AI-based methods for English speech recognition
Temporal dependency modeling in real-time data streams using a deep learning model
Predictive analytics for financial fraud detection and risk management
Data science in manufacturing for cost reduction and efficiency
AI-driven agricultural analytics
Featuring such advanced modeling techniques as predictive modeling, simulation, and optimization algorithms, the book presents innovative solutions that emphasize benefits and practicality. With its emphasis on interdisciplinary applications, it showcases successful projects that underscore the synergy between AI and data science domains, empowering readers to harness the power of innovation for enhanced problem-solving and efficiency in interdisciplinary realms.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Professional Practice & Development and Professional Reference
Illustrations
12 s/w Tabellen, 83 s/w Abbildungen, 83 s/w Zeichnungen
12 Tables, black and white; 83 Line drawings, black and white; 83 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 22 mm
Weight
661 gr
ISBN-13
978-1-032-89465-2 (9781032894652)
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
D. Sivabalaselvamani | G. Revathy | Ranjit Singh Sarban Singh
Advanced AI and Data Science Applications
E-Book
09/2025
Auerbach
€218.99
Available for download
D. Sivabalaselvamani | G. Revathy | Ranjit Singh Sarban Singh
Advanced AI and Data Science Applications
E-Book
09/2025
Auerbach
€218.99
Available for download
Persons
Dr. D. Sivabalaselvamani is an associate professor in the School of Information Science, Presidency University, Bengaluru, Karnataka, India.
Dr. G. Revathy is an assistant professor in the Department of CSE, SASTRA Deemed University, Kumbakonam, India.
Dr. Ranjit Singh Sarban Singh is an associate professor in the Department of Computing and Information Systems, School of Engineering and Technology, Sunway University, Malaysia.
Dr. G. Revathy is an assistant professor in the Department of CSE, SASTRA Deemed University, Kumbakonam, India.
Dr. Ranjit Singh Sarban Singh is an associate professor in the Department of Computing and Information Systems, School of Engineering and Technology, Sunway University, Malaysia.
Content
1. Metaheuristic Optimization Techniques for Solving Complex AI Model Training Challenges 2. AI and Data Science: Transforming IPL Strategy and Success 3. Augmenting Human Creativity: An Assessment AI in Art and Music Generation 4. Building Tomorrow's Cities: The Impact of AI and Data Science on Urban Development 5. Implementing AI for Enhanced Cybersecurity Iin Industrial Control Systems 6. A Comparative Study of Traditional and AI-Based Methods for English Speech Recognition 7. Smart Gene Editing: AI and DS to Improve CRISPR-Cas9 Outcomes in Disease Therapy 8. Polarizing Sentiments: A Comprehensive Analysis of Social Media Content Using Text Extraction and Sentiment Polarization 9. Deep Learning Approaches for Skin Disease Detection: A Comprehensive Review 10. Transforming Healthcare with Blockchain: A Review of Security, Efficiency, and Resource Allocation Strategies 11. Temporal Dependency Modeling in Real-Time Data Streams Using a Deep Learning Model 12. Enhancing Bone Cancer Detection Using AI-Based Multi-Model Ensemble Deep Learning Techniques 13. Hand Sign and Gesture Recognition Using Deep Learning 14. Artificial Intelligence and Data Science: An Overview 15. Enhancing Rainfall Prediction: Optimizing XGBoost with Bayesian Hyperparameter Tuning (OPXGB) 16. AI in Finance: Predictive Analytics for Fraud Detection and Risk Management 17. Optimizing Supply Chains with AI: Data Science in Manufacturing for Cost Reduction and Efficiency 18. AI-Driven Agricultural Analytics: Enhancing Sustainability and Productivity through Data Science 19. Data Science in Fintech: Transforming Financial Services with Machine Learning and AI 20. Balancing AI Security and Access: Ethical Considerations in Deploying AI Models