Skills used: R, Random Forest, XGBoost, Scenario Testing

Skills used: R, Multinomial Logistic Regression, App Wireframe, Profit Optimization

Skill used: Python, Keras, CNN, VGG16

Skills used: Python, Web Scraping, Twitter API, Sentiment Analysis, Street Network Analysis (Pandana), Machine Learning (Scikit-learn), Data Visualization (Altair, HvPlot, Seaborn, Folium, Panel)

Skills used: R, Poisson Regression Model

Skills used: R, OLS Modeling, Spatial Lag

Skill used: Python, Tensorflow

Skill used: Python, beautifulsoup

Skill used: Python, rasterio, rasterstats

Skill used: ArcMap

Skills used: Javascript, Leaflet, HTML, CSS

Skills used: Javascript, Leaflet, Billboard, HTML, CSS

Skill used: Python, datashader

Predict Philadelphia house values with spatial lag, spatial error and geographically weighted regression (GWR).

Skill used: Python, Machine Learning (Scikit-learn), K-Means, SVM, Deep Learning (Keras), Convolutional Neural Network (CNN), ResNet

Find the viable forest patches that are of the most conservation importance through patch analyses. Skill used: Google Earth Engine

Evaluate the fairness of algorithms in predicting recidivism.