Dynamic Pricing is an application of data science that involves adjusting the prices of a product or service based on various factors in real time. This project implements a dynamic pricing strategy for a ride-sharing service using Python.
- Data analysis and visualization
- Dynamic pricing algorithm implementation
- Machine learning model for price prediction
- Profitability analysis
Run the Jupyter notebook for exploratory analysis: jupyter notebook notebooks/dynamic_pricing_analysis.ipynb To train the model: python src/model_training.py To make predictions: python src/predict.py
The dataset used in this project contains information about: Number of riders Number of drivers Vehicle type Expected ride duration Historical cost of rides
Our dynamic pricing strategy achieved [X]% improvement in profitability compared to fixed pricing.