A collection of my best projects. Real world projects with real data that help solve a problem.
Discipleship Tracker helps church leaders visualize the depth and health of discipleship across their congregation. It tracks one-on-one discipleship relationships and surfaces patterns that are otherwise hard to see at scale.
In ProgressCheck Your Gauges helps users stay consistent and self-aware across the four dimensions that matter most to a healthy leader: Mental, Spiritual, Relational, and Physical. The app provides a simple daily check-in experience so that patterns and gaps become visible over time.
Visit Site →Is there a way to predict the next 311 call using machine learning? It turns out it is. In this project I was able to predict with a 85% accuracy the next 311 call topic, response time, and city
View on GitHub →To succesfully use this project, you need a large compilation of images that are separated in at least 2 folders, each folder representing a class to be classified. The images need to be stored on a local directory. For this project we have two folders stored locally one with pictures of cars , obtained from Kaggle, and another file of pictures that are not cars, obtained from the Visual Genome.
View on GitHub →The English Premeire Legue is the best league in the world right now. Has been named the best league in the world three years in a row. It consists of 20 teams. The prediction of the premiere league is an ongoing project by STU Big Data. Early versions of the predictor delt with team data as a whole. My version of the predictor uses data from all the players.
View on GitHub →Is there a way to predict the stock market? In this project we attempted to do so as part of a Fantasy Stock competition. Using prediction models and machine learning algorithms, my team and I where able to accurately predict and make more than 250 successful buy/sell decisions each day of the competition.
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