The official Python client library for the ParityVend API. Add location-based pricing to your Python applications and take your business to a global level.
E-commerce pricing optimization & dynamic user profiling
A machine learning project that uses an XGBoost model to predict optimal pricing strategies for Walmart products, incorporating confidence scores.
ML-powered pricing optimization for UK coffee shops. R²=0.997 accuracy with weather integration, SHAP explainability, and ethics guardrails. Historical backtest proves 16% margin lift (£17,959 annual opportunity).
End-to-end E-Commerce analytics system for revenue forecasting, dynamic pricing optimization, explainability (SHAP), and model drift detection — built using Python, Machine Learning, and Streamlit.
Comprehensive market analysis of Athens Airbnb listings delivering actionable Tableau insights for strategic decision-making.
End-to-end Price Optimization Engine using Random Forest. Simulates price elasticity and competitor data to prescribe optimal pricing strategies for revenue maximization. Built with Python & Streamlit.
contains our team submission for Hackathon Bank Indonesia. Problem that we want to solve is the unfairness of fish price. In summary, we propose to (1) using geospatial ML when to decide the next location of cold storage (2) build app to help fish auction decide the fair price and monitor the recommended storage location based on stock management
Data-driven SaaS pricing optimization using ML to maximize LTV/CAC ratios. Employs Random Forest, clustering, and elasticity analysis on 4,222 customers to recommend tiered pricing strategies that balance revenue growth with sustainable churn rates.
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