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.
The book explores advancements in Artificial Intelligence (AI) and data science for various domains. Looking at these technologies’ transformative impact on developing application, the book blends theory and practice to serve as a roadmap for understanding how these technologies are applied.
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 Tomorrows 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
Dr. D. Sivabalaselvamani is an associate professor in the Department of Computer Applications, Kongu Engineering College, Perundurai, 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.
