This is my technology stack

Python

R

SQL

ArcGIS

Google Earth Engine

Jupyter Notebooks

Git

QGIS

Here are some of my projects

• 

  Employee Salary Prediction

  Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn

  Created a regression model with MSE score of 355 on employee salary data given their corresponding qualifications and role descriptions to help employers/recruiters determine suitable salaries for potential candidates.
• 

  Hamilton House Price Prediction

  Scikit-Learn, GeoPandas, PySal, NumPy, Matplotlib, Seaborn

  Created a tool that estimates house prices (MSE ~ $57070.99, R^2 ~ 0.805) to help predict house prices by census tract in the city of Hamilton, ON. Created a spatial regression tool that estimates house prices (R^2 ~ 0.8548, MSE ~ 0.02 on Log transformed data) based on the location of census tracts in Hamilton, ON.
• 

  Nuclear Bomb Deployment Classifier

  Scikit-Learn, Pandas, NumPy, Pandas, Seaborn

  Created a multiclass classification model with 92% accuracy using imbalanced classification techniques on nuclear bomb explosions data to help third-party inspectors determine the deployment method of a given nuclear bomb.