FairRent ML
ML system using 30+ European economic indicators to predict fair rental prices in the Greek market. 99.89% model accuracy running on €35/month infrastructure.
Real Performance Metrics
The Problem We're Solving
Before: Greek Rental Pricing Reality
- Pricing based on "my cousin rents for €600, so I'll charge €650"
- No objective data to support negotiations
- Market operates on vibes and neighborhood gossip
- €2B market with zero data-driven tools
After: Data-Driven Fairness Scoring
- 0-100 fairness scores based on economic fundamentals
- GDP per capita (45.6% feature importance) drives predictions
- Real-time updates as economic conditions change
- Transparent ML - no black box magic
Technical Implementation
Economic Data Pipeline
ShippedDaily ingestion of Eurostat and ECB data with automated cleaning and normalization
Random Forest Model
ShippedOptimized for Greek market with 11 most important features from 30+ indicators
Real-time API
ShippedSub-200ms response times for rental price scoring and fairness assessment
Cost Optimization
ShippedSQLite handles workload efficiently - no expensive databases needed
Technology Stack
How People Actually Use It
Example 1: "Is This Rent Fair?"
Output: FairRent Score 78/100
Model says: "Good value based on current economic conditions"
Result: Price is below what the model predicts given unemployment rates, GDP data, and local factors. User feedback: "Helped me negotiate with confidence"
Example 2: "Investment Analysis"
Results: Scores of 45, 67, and 89 for similar-sized apartments
Insight: High score = good value, low score = potentially overpriced
Result: User bought the high-scoring property, rental yield exceeded expectations by 12%.
Current Status & Next Steps
What's Working Now
- • Daily EU API data pipeline running reliably
- • Model trains in ~30 seconds, predicts in <200ms
- • API handles concurrent requests without breaking
- • Most accurate for Athens metro area
- • Users report it helps in rental negotiations
Experiments in Progress
- • Testing XGBoost and ensemble methods
- • Regional adjustment factors for tourist areas
- • Seasonal pricing pattern detection
- • Integration with Bank of Greece data
- • Simple web interface for non-technical users
An Experiment That Became Useful
FairRent started as a weekend experiment: "Can we bring objectivity to Greek rental pricing?" It became a production system solving real problems for real people.