reibena/NUS-Datathon-2024
Predicting Singlife Clients' Purchasing Behaviors With Python: Won 2nd Place in NUS's biggest Data Science competition with > 900 participants
This project helps insurance companies or financial institutions predict which existing clients are most likely to purchase new products. By analyzing client data, it identifies key factors influencing purchasing decisions and outputs a prediction of whether a client will buy or not. This is for data analysts or business intelligence specialists in the insurance or finance sector who need to identify sales opportunities.
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Use this if you have an imbalanced dataset of customer purchasing history and need a robust way to predict future buying behavior.
Not ideal if you need a model that can explain every prediction using only the original features without any transformation or simplification.
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Jupyter Notebook
License
MIT
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Last pushed
Nov 11, 2024
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