Del i serien Advances in Computational Collective Intelligence

Advanced AI and Data Science Applications

Inbunden, Engelska, 2025

AvD. Sivabalaselvamani,G. Revathy,Ranjit Singh Sarban Singh

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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 challengesThe impact of AI and data science on urban developmentImplementing AI for enhanced cybersecurity in industrial control systemsA comparative study of traditional and AI-based methods for English speech recognitionTemporal dependency modeling in real-time data streams using a deep learning modelPredictive analytics for financial fraud detection and risk managementData science in manufacturing for cost reduction and efficiencyAI-driven agricultural analyticsFeaturing 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.

Produktinformation

Utgivningsdatum2025-09-24
Mått156 x 234 x 22 mm
Vikt770 g
FormatInbunden
SpråkEngelska
SerieAdvances in Computational Collective Intelligence
Antal sidor16
FörlagTaylor & Francis Ltd
ISBN9781032894652

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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.

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