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Project9_ExcelR - The Warrenty Claim Project

During my Training period at ExcelR Solutions.

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Project Objective:

To predict whether the warranty claim filed by a customer is fraud or genuine.

Methods and Algorithms:

Decission tree, XGBoost 0.90, CatBoost 0.19.1, Random Forest.

Tools and Techniques:

Python 3.6.5, Flask (deployment), Heroku (hosting).

Brief description about the project:

In this project I worked on the data of a Electronics company who sells TV and AC all over India. Using the tree-based models mentioned above I come up with more than 0.96 accuracy, so I considered them for my Model deployment, where I used the Flask module. And for showcasing my model I hosted my models using Heroku.

ExcelrProject9-link