The book provides comprehensive and in-depth exploration of how soft computing techniques can be applied in the domain of business analytics. The book shows these techniques can be leveraged to extract valuable insights from vast and complex datasets to enable businesses to make data-driven decisions for improve competitive advantage.
The book provides comprehensive and in-depth exploration of how soft computing techniques can be applied in the domain of business analytics. The book shows these techniques can be leveraged to extract valuable insights from vast and complex datasets to enable businesses to make data-driven decisions for improve competitive advantage.
Nitendra Kumar, PhD, is an assistant professor at the Amity Business School, Amity University, Noida, India. Lakhwinder Kaur Dhillon, PhD, is an associate professor and specialized faculty member in corporate finance, strategic financial management, accounting for managers and international finance and Forex management at Amity University, Uttar Pradesh, India. Mridul Dharwal, PhD, is a professor of economics in the Management Department, School of Business Studies, Sharda University, Uttar Pradesh, India. Elena V. Korchagina, PhD, is a professor at Peter the Great St. Petersburg Polytechnic University, Institute of Industrial Management, Economics and Trade, St. Petersburg, Russia. Vishal Jain, PhD, is an associate professor at Sharda University, Uttar Pradesh, India.
Inhaltsangabe
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
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
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