https://github.com/tsu2000/insurance

Machine learning web app in Streamlit about predicting insurance charges using various regression models.
https://github.com/tsu2000/insurance

logistic-regression machine-learning plotly python random-forest regression streamlit-webapp

Last synced: about 1 year ago
JSON representation

Machine learning web app in Streamlit about predicting insurance charges using various regression models.

• Host: GitHub
• URL: https://github.com/tsu2000/insurance
• Owner: tsu2000
• License: mit
• Created: 2023-01-16T13:32:24.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-08-18T16:15:41.000Z (almost 2 years ago)
• Last Synced: 2025-01-23T03:41:36.516Z (over 1 year ago)
• Topics: logistic-regression, machine-learning, plotly, python, random-forest, regression, streamlit-webapp
• Language: Python
• Homepage: https://insurance-ml.streamlit.app
• Size: 679 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# insurance

A simple web application for exploring various regression models to predict insurance charges based on customer data.



Users can further tune the hyperparameters these models to observe changes in the results, interact with data to predict possible charges, and view a basic exploratory data analysis (EDA) of the data provided. Current machine learning algorithms available in the app include:

- Linear Regression

- Ridge Regression

- Lasso Regression

- Decision Tree Regression

- Random Forest Regression

**Link to Web App**:

[]()