PART I: Overviews
1. Machine Learning
2. Regression Methods
3. Functional Data Analysis
4. Directional Data Analysis
5. Branching Processes
PART II: PREDICTIVE ANALYTICS APPLICATIONS
6. Click-Through Rate Estimation using CHAID Classification Tree Model
7. Predicting Success Probability in Professional Tennis Tournaments: Using a Logistic Regression Model
8. Hausdorff Path Clustering and Hidden Markov Model Applied to Person Movement Prediction in Retail Spaces
9. Improving Email Marketing Campaign Success Rate Using Personalization
10. Predicting Customer Churn for DTH: Building Churn Score Card for DTH
11. Applying Predictive Analytics in a Continuous Process Industry
PART III: MACHINE LEARNING APPLICATIONS
12. Automatic Detection of Tuberculosis using Deep Learning Methods
13. Connected Cars and Driving Pattern: An Analytical Approach to Risk Based Insurance
14. Hybrid Machine Learning and Cognitive approach using Telematics and IoT for Tackling Downtime of Commercial Vehicles and Taxis
PART IV: HUMAN RESOURCE ANALYTICS
15. Analytics-led Talent Acquisition for Improving Efficiency and Effectiveness
16. Assessing Student Employability to Help Recruiters Find the Right Candidates
PART V: OPERATIONS ANALYTICS
17. Innovative Heuristics Modeling for Dynamic Project Cost Optimization
18. Estimation of Fluid Flow Rate and Mixture Composition using Low Cost Acoustic Sensors for Application in the Oil and Gas Industry
PART VI: ANALYTICS IN FINANCE
19. Loan Loss Provisioning Practices in Indian Banks
20. Modeling Leptokurtic Return Distributions in Commodity Markets
PART VII: METHODOLOGY
21. OLS: Is That So Useless for Regression with Categorical Data?
22. Estimation of Parameters of Misclassified Size Biased Borel
23. A Stochastic Feedback Queuing Model with Encouraged Arrivals and Retention of Impatient Customers
PART VIII: ECONOMETRIC APPLICATIONS
24. Does Banking Competition Granger Cause Banking Stability: The Study of SEM Countries
25. The Relationship Between Insurance and Economic Growth in India: A Cross-region Study Using an Econometric Approach
About the Author: Prof. Arnab K Laha takes keen interest in understanding how analytics, machine learning and artificial intelligence can be leveraged to solve complex problems of business and society. His areas of research and teaching interest include Advanced Data Analytics, Quality Management and Risk Modeling. He has published papers in national and international journals of repute in these areas and has served on the editorial board of several journals including Statistical Analysis and Data Mining: The ASA Data Science Journal. He was featured among India's best business school professors by Business Today in 2006 and Business India in 2012 and was named as one of the "10 Most Prominent Analytics Academicians in India" by Analytics India Magazine in 2014 and 2017. He is the convener of the biennial IIMA series of conferences on Advanced Data Analysis, Business Analytics and Intelligence. He is the author of the popular book on analytics entitled "How to Make the Right Decision" published by Penguin-Random House. He has conducted large number of training programmes and undertaken consultancy work in the fields of business analytics, quality management and risk management.