- 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.
- 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.
- Create a new environment
python -m venv env
- Activate the new environment
(powershell)
.\env\Scripts\Activate.ps1
- Install required packages
pip install -r requirements.txt
- Now run main.py
python main.py
- Now run the app
streamlit run app.py
Provide a link and a sample video and also the link of the HLD documents
- Ravi Kumar