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

2. Activate the new environment

(powershell)
.\env\Scripts\Activate.ps1 

3. Install required packages

pip install -r requirements.txt

4. Now run main.py

python main.py

5. 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 👨🏼‍💻

• Ravi Kumar