
Advanced AI and Data Science Applications
Series: Advances in Computational Collective Intelligence;
- Publisher's listprice GBP 155.00
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Availability
Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
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Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher Auerbach Publications
- Date of Publication 24 September 2025
- ISBN 9781032894652
- Binding Hardback
- No. of pages328 pages
- Size 234x156 mm
- Weight 770 g
- Language English
- Illustrations 83 Illustrations, black & white; 83 Line drawings, black & white; 12 Tables, black & white 918
Categories
Short description:
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.
MoreLong 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.
MoreTable of Contents:
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
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