- ホーム
- > 洋書
- > 英文書
- > Computer / General
Full Description
Intelligent Business Analytics: Harnessing the Power of Soft Computing for Data-Driven Insights explores the transformative role of soft computing methods in improving business analytics. It looks at how intelligent analytical methods can be applied to complex business data to derive meaningful insight. It focuses on integrating such intelligent technologies as neural networks, fuzzy logic, genetic algorithms, AI, machine learning, and deep learning, to data analytics. The book examines:
Fundamental concepts of soft computing and its role in data analysis
How neural networks and deep learning techniques can be used to analyze complex data patterns to make more accurate predictions
Swarm intelligence techniques that can help identify hidden patterns in customer data and optimize marketing strategies
Combining multiple soft computing techniques to create hybrid models for business recommendation systems
Using machine learning techniques to analyze user behavior and brand interactions to provide personalized brand recommendations
Advanced visualization techniques to interpret the complex results of soft computing models.
Other topics include predictive analytics, customer segmentation, real-time decision support systems, and soft computing to handle uncertainty, ambiguity, and dynamic data environments. Each chapter provides theory as well as an applied example, making the book a roadmap on how to leverage computational intelligence in diverse areas of business decision-making.
Contents
1. Soft Computing Paradigms: A Gateway to Intelligent Data Analysis 2. An Overview of Prophesying Line of Work through Networks and Deep Learning 3. Machine Learning-based Market Segmentation with Data Mining for Proficient Data Driven Business 4. Versatility of Neural Networks in Business Data Analytics: Comprehensive Review and Future Directions 5. Neural Networks and Deep Learning in Predictive Modelling 6. Swarm Intelligence in Customer Segmentation 7. Data-Driven Insights for Decision-Making in the Stock Market by Using Meta-Analyses 8. Hybrid Soft Computing Approaches for Business Recommendation 9. Enhancing Personalized Brand Recommendations through Machine Learning-Driven Analysis of User Behavior and Brand Interaction 10. Advanced Visualization Techniques for Soft Computing Results 11. Embroilment of Deep Learning in Business Analytics for Sustainable Growth 12. Application of Soft Computing in Business Analytics: A Journey into Intelligent Data Insights 13. Applications of Deep Learning Techniques in Businesses: Challenges and Opportunities for Data Integration 14. Harnessing Artificial Emotional Intelligence for the Improvement of Teaching Learning Process in Digital Classroom 15. Education and Training Revolution: A Review on AR, VR, and IoT Integration in Educational Perspective 16. Leveraging Artificial Intelligence and Machine Learning for Enhancing Financial Inclusion Opportunities, Challenges, and Ethical Considerations
