Description
Book SynopsisRamesh Sharda (MBA, PhD, University of WisconsinMadison) is Vice Dean for Research and Graduate Programs, Watson/ConocoPhillips Chair, and Regents Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University. His research has been published in major journals in management science and information systems, including Management Science, Operations Research, Information Systems Research, Decision Support Systems, Decision Sciences Journal, EJIS, JMIS, Interfaces, INFORMS Journal on Computing, and ACM Database. Dr. Sharda is a member of the editorial boards of journals such as Decision Support Systems, Decision Sciences, and ACM Database. He has worked on many sponsored research projects with government and industry, and has been a consultant to many organizations. He also serves as the faculty direc
Table of Contents
- PART I: INTRODUCTION TO ANALYTICS AND AI
- 1. An Overview of Business Analytics, Decision Support Systems, Business Intelligence, Data Science, and Artificial Intelligence
- 2. Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications
- 3. Nature of Data, Statistical Modeling, and Visualization
- PART II: PREDICTIVE ANALYTICS AND MACHINE LEARNING
- 4. Data Mining Process, Methods, and Applications
- 5. Machine learning Techniques for Predictive Analytics
- 6. Deep Learning and Cognitive Computing
- 7. Text Mining, Sentiment Analysis, and Social Analytics
- PART III: PRESCRIPTIVE ANALYTICS AND BIG DATA
- 8. Prescriptive Analytics with Optimization and Simulation
- 9. Big Data, Location Analytics, and Cloud Computing
- PART IV: ROBOTICS, SOCIAL NETWORKS, AI, AND IoT
- 10. Robotics: Industrial and Consumer Applications
- 11. Group Decision Making, Collaborative Systems, and AI Support
- 12. Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal Assistants, and Robo Advisors
- 13. The Internet of Things As a Platform for Intelligent Applications
- PART V: CAVEATS OF ANALYTICS AND AI
- 14. Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts
