Market Modeling · Python & AI · ROI

Muratpaşa Investment

An AI-powered real estate investment analysis for Antalya's Muratpaşa district — with a live valuation demo.

The Challenge

Accurate pricing and investment-zone selection in real estate usually rely on subjective judgment or outdated methods. In a dynamic district like Muratpaşa, Antalya, it wasn't clear which property type — combined with which elevation and view profile — would deliver the highest rental return. Manual valuation errors were directly cutting into investor profitability.

Data Quality & Methodology

I cleaned raw January 2024 listing data — removing faulty entries, duplicates, and outliers — to build a reliable analytical foundation. Each neighborhood was then scored on custom-defined metrics: Elevation (0–2) and View Potential (0–2), capturing factors that standard listings data doesn't surface on its own.

Analysis Steps

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Topographic & Social Segmentation

The district was split by elevation level. Low elevation (Level 0) proved to have the strongest rental power, averaging 26,250 TL.

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ROI Mapping

8 key neighborhoods were identified (Yeşilbahçe, Şirinyalı, and others). Yeşilbahçe set the district record at 466 TL per m².

AI-Powered Valuation — Live Demo

Manual valuation is slow and error-prone. The model below analyzes thousands of data points in seconds to generate a rental valuation — try it directly.

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Project Details

Role Data Analyst & Developer
Data Period January 2024
Toolkit
Python Outlier Detection ROI Modeling K-Means Clustering

rocket_launch Open Live Demo

Strategic Findings

87,500 TL

Max. Rental Return (Yeşilbahçe)

36%

Ideal Property Type (3+1, Gated Community)

Summary

For investors, the sweet spot is properties with an elevation score of at most 1 and a view score of at least 1 — these deliver the fastest and highest returns. Furnished 3+1 apartments within gated communities show particularly strong pricing power along the Şirinyalı and Fener corridor.