A simple Streamlit WebApp, which can predict Car Price with Machine Learning Models such as Linear Regression, Ridge Regression, and Lasso Regression.
I've also trained this using Neural Network.
git clone https://github.com/somanathkshirsagar/LeastSquare.gitPrerequisite - Docker
- Build Docker Images
docker build -t leastsquare:latest .- Run App in Docker Container
docker run leastsquare:latestPrerequisite - Conda, Python
- Create a Conda Virtual Environment
conda create -n leastsquare- Activate Virtual Environment
conda activate leastsquare- Install Requirements.txt
pip install -r requirements.txt- Run Streamlit App
streamlit run app.pyThis data was scraped from cars24.com.
I used Octoparse to scrape the data from the website.
- Name
- Variant
- Transmission
- km_driven
- Owner_Type
- Fuel
- Price
- Age (Derived from Year Purchased)
