Sentiment Analysis of NFL Quarterback Using Twitter APIs and R

Sports fans across the country regularly discuss their favorite teams, players, coaches, etc. throughout each sports season. After all, a common passion connects people — and sports often bring people together. With so many opinions across different teams, what if we wanted to better understand...

Domesticated Animal Image Classification with Python

In this use case, my colleagues and I collaborated on creating and optimizing a convolutional neural network in order to identify domesticated animals versus non-domesticated animals to assist in funding suggestions for local animal shelters. Using the CIFAR-10 dataset with over 60,000 images,...

Using R Shiny to Inform Community Officials

Using a leaflet interactive map, we created a multilevel, informational dashboard that enables community officials to develop better insights into their population, facilities, and areas in need. This project utilized data from Census reports, facilities information, housing, and abandoned...

Identifying Malignant Tumors with Machine Learning

Using data centered around the measurement of a variety of tumors, we created 3 machine learning models and compared the performance of each in classifying tumors as malignant or benign. We catered our approach, explanation, and demo towards medical professionals and explained a variety of model...

Creating Customer Segmentations Predictions App with KMeans

Using Pycaret to create a quick-n-easy KMeans model and deploying this model using Streamlit. Model deployed includes a GUI that enables the end user to add in a given data point to be classified into a cluster based on model predictions.