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insurance-premium-prediction's Introduction

Insurance Premium Prediction Application

  • This repository represents " Insurance premium prediction according to his/her conditions ".
  • With the help of this project we can tell that how much insurance can be get based on the his/her conditons.

Description

  • This is regression project.
  • In this project we have used various algorithms as follows: Linear regression
    Ridge regression Lasso regression Polynomial regression Random Forest regression Gradient Boost regression XGBoost regression LGBoost regression CatBoost regression
  • In this project we have GridSearchCV to find the best parameters.
  • Top best 4 models picked according to the training set.
  • Finally the best model is picked, that best performs on the test set out of these 4 models.
  • The source code from data ingestion to model pusher is written in src folder in the repo.

How to run

  1. Create a new environment
python -m venv env
  1. Activate the new environment
(powershell)
.\env\Scripts\Activate.ps1 
  1. Install required packages
pip install -r requirements.txt
  1. Now run main.py
python main.py
  1. Now run the app
streamlit run app.py

Inference demo

Provide a link and a sample video and also the link of the HLD documents

Contributors ๐Ÿ‘จ๐Ÿผโ€๐Ÿ’ป

  • Ravi Kumar

insurance-premium-prediction's People

Contributors

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