Paperback : HK$340.00
This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis.
Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively.
This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.
Show moreThis book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis.
Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively.
This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.
Show more1. Concepts for Effective Mobile Devices Management in Enterprise Environment. 2. Prioritization of Informational Factors and Query Intensification Using Meta-heuristic Approach. 3. Estimation and Potential Evaluation of Data Linked to Virtual Machines Using Computational Approach. 4. Potential Applications of Blockchain Technology in Construction Sector. 5. Artificial Neural Networks Applications in Social Media Activities Impact on Depression During the COVID-19 Pandemic. 6. Analysis of CCT through ANFIS for Grid Connected SPV System. 7. Frequency Analysis of Human Brain Response to Sudarshan Kriya Meditation. 8. Coordinated Control Action Between DFIG-Grid Interconnected System Using PI Based SVM Controller. 9. Acceptance of New School in Semi-Urban Areas of India: An Application of Data Mining. 10. Two- Phase Natural Convection of Dusty Fluid Boundary Layer Flow Over a Vertical Plate. 11. An Interactive Injection Mold Design with CAE and Moldflow Analysis for Plastic Components. 12. Study of Collaborative Filtering based Personalized Recommendation Quality, Relevance and Timing Effect on Users’ Decision to Purchase.
Zdzislaw Polkowski is presently associated with Department of Business Intelligence in Management, Wroclaw University of Economics and Business, Poland.
Sambit Kumar Mishra is presently associated with the Gandhi Institute for Education and Technology, Baniatangi, Bhubaneswar, Odisha, India.
Julian Vasilev is presently associated as Professor in University of Economics, Varna, Bulgaria.
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