Machine Learning Platform

A mining exploration firm had observed a pattern of high mineral occurance in areas with larger trees but didn't have a way of proving the causality given the multitude and complexity of factors contributing to both large trees and mineral deposits.

• Worked with a team of geologists to identify relevant data sets of environmental and geological factors.
• Cleaned and transformed data suitable for input into a machine learning tool.
• Developed, trained, and tested a suite of models using the data provided to understand the relationship between environmental factors and mineral deposits.

Based on known mineral occurances, the "Big Tree" hypothesis was validated; A second model was developed that inverted the question to predict mineral concentrations based on tree height that was not already accounted for by environmental factors.