https://github.com/b-pinter/b-pinter

About Me Section
https://github.com/b-pinter/b-pinter

about-me information

Last synced: 5 months ago
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About Me Section

• Host: GitHub
• URL: https://github.com/b-pinter/b-pinter
• Owner: b-pinter
• Created: 2023-11-28T21:37:31.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2026-01-15T03:44:44.000Z (6 months ago)
• Last Synced: 2026-01-15T09:42:12.911Z (6 months ago)
• Topics: about-me, information
• Homepage: https://github.com/b-pinter
• Size: 10.7 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
Hi, I'm Brady Pinter! 👋

- I'm a senior at Belmont University majoring in Data Science with minors in Business Systems and Analytics and Communications. I am interesting in learning more about machine learning and bayesian statistics, and applying things I have learned across a wide variety of projects.

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🎯 Current Work

- One of my major projects right now is about Tommy John Surgery, a common issue that many MLB pitchers face. The goal of this project is to use bayesian methods and a hierarchial model to predict and avoid the surgery when possible.

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🛠️ Skills

- Programming Languages : Python, R, SQL

- Tools and Libraries : Git, Matpollib, Seaborn, ggplot2, Scikit-Learn, STAN

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**🚀 Featured Projects**

Tommy John Surgery Prediction Model

- A comprehensive fullstack application designed to predict UCL (ulnar collateral ligament) injuries in MLB pitchers using live-tracked pitch data from 2020 onwards. This project combines advanced machine learning techniques with real-time baseball analytics to help identify injury risk factors and potentially prevent career-threatening injuries.

**Key Features:**

- Integration of live pitch-tracking data

- Predictive modeling for injury risk assessment

- Full-stack development with data pipeline automation

COVID-19 Mortality Rate Prediction

- An independent research project analyzing the impact of socio-economic factors on COVID-19 mortality rates across the United States. Utilized multiple regression techniques including Least-Squares, Ridge, and Lasso Regression to identify key indicators affecting mortality outcomes.

**Key Insights:**

- Analyzed publicly available social and economic indicators

- Compared performance of various regression models

- Identified significant correlating factors in mortality rates.

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📫 Connect with me!

- LinkedIn: www.linkedin.com/in/brady-pinter