iyashk/Car-Price-Prediction

A Machine Learning Project that uses Random Forest Regressor model to predict used cars price based on some attributes such as kilometers driven, age, number of previous owners etc.

26
/ 100
Experimental

The model pipeline includes data preprocessing to handle mixed categorical and numeric features, followed by training a serialized pickle artifact for deployment. A Flask web application provides real-time inference through an HTML interface, accepting user inputs for car attributes and returning predicted prices. The project uses scikit-learn for model implementation and relies on Conda for dependency management across a Python 3.6 environment.

No commits in the last 6 months.

No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 1 / 25
Community 18 / 25

How are scores calculated?

Stars

27

Forks

14

Language

Jupyter Notebook

License

Last pushed

Feb 08, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/iyashk/Car-Price-Prediction"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.