⛏ GeoAI Mineral Prospectivity Mapping

Machine Learning • Economic Geology • Mineral Exploration

GeoAI Python Machine Learning Mineral Exploration Geospatial Analysis

Project Overview

This GeoAI project demonstrates how geological indicators such as structural proximity, alteration intensity, and geochemical anomalies can be integrated with machine learning models to highlight potential mineral prospectivity zones.

Global Mineral Zones

Potential Mineral Province
Regions: 5
Model: Random Forest
Dataset: 1200 samples
Accuracy: 98%

Model Outputs

Methodology

• Geological feature simulation • Structural proximity analysis • Random Forest classification • Mineral prospectivity visualization

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