Description Dear Participants, Please submit your project notes -2 here

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Description

Dear Participants,

Please submit your project notes -2 here.

 

Problem Statement:

Life Insurance Data The dataset belongs to a leading life insurance company. The company wants to predict the bonus for its agents so that it may design appropriate engagement activity for their high performing agents and upskill programs for low performing agents.

Review Parameters	Review Points
1). Model building and interpretation.	10
a. Build various models (You can choose to build models for either or all of descriptive, predictive or prescriptive purposes)
b. Test your predictive model against the test set using various appropriate performance metrics
c.Interpretation of the model(s)
2). Model Tuning and business implication	10
a.Ensemble modelling, wherever applicable
b. Any other model tuning measures(if applicable)
c. Interpretation of the most optimum model and its implication on the business
Total	20

 

Please note the following:

• You have to submit 2 files : 
   
  1. Business Report: In this, you should cover all the topics given in the rubric in a sequential manner. It should include a detailed explanation of the approach used, insights, inferences, all outputs of codes like graphs, tables, etc. and their business implications. Your report should not be filled with codes. You will be evaluated based on the business report.
  2. Python Notebook file: This is a must and will be used for reference while evaluating.Failing to do so shall lead to ZERO marks in all the sections where code file is necessary.
• Please note that evaluation will happen on Business Report. The Python-code is only for reference. If you fail to submit the Business report ZERO Marks will be awarded.
• Any notes found copied/ plagiarized with other(s) will not be graded and marked as zero.
• Please ensure timely submission as the post-deadline assignment will not be accepted.

Standard Instructions for Business Report:

• All pages must be numbered.
• Tables/figures/charts/graphics (if any) must have number and title.
• Groups must make sure visualizations are clearly read at usual magnification and add value to the Report
  • All visualizations must be clearly labelled.
  • All axis labels and legends must be legible.
  • Tableau graphics default mode is not always conducive to normal copy-paste. A proper adjustment may be required. 

All raw codes and raw outputs must be in the Appendix. Illegible graphs and raw codes and raw outputs in the body of the report will mandate a heavy penalty.