Mohshaikh23/Dynamic-Pricing-Strategy

Adjusting the prices of a product or service based on various factors in real time

31
/ 100
Emerging

Implements demand-driven pricing for ride-sharing using a Random Forest Regressor trained on historical ride data, with inputs for rider/driver supply ratios, vehicle type, and duration. Built as a Streamlit web application, it generates interactive Plotly visualizations comparing predicted prices against actuals and profiles ride profitability distribution. Includes data preprocessing to handle missing values and accepts CSV datasets for model retraining.

No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 9 / 25
Community 16 / 25

How are scores calculated?

Stars

20

Forks

6

Language

Jupyter Notebook

License

MIT

Last pushed

Aug 14, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Mohshaikh23/Dynamic-Pricing-Strategy"

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