Project Name: ROGER FEDERER VS THE WORLD
Classification Modeling Project. A capstone group project where we are taking data from the last 20 years of professional men's tennis and exploring to identify drivers of win. Using modern machine learning algorithms, the Racket Science team aims to predict the outcome of future matches. We are also delving into the career stats of Roger Federer whom some considered to be the best to ever play the game. We are discovering his drivers of greatness and comparing those drivers to his top rivals to see if he is truly unmatched or if he has been dethroned. We are also exploring the first 50 games of Federer and his rivals to determine if their rise to tennis fame could have been predicted early on.
My background in Reverse Engineering of Malware and Digital Forensics brings a unique perspective to my creative process as a Data Scientist. Solution-Oriented and always learning, I set my eyes on a goal and always get there.
taking something essentially meaningless like a pile of data, and molding it into something that is not only meaningful but can impact how we interact with the world around us.
San Antonio, TX | Remote
Creative, Resourceful, and Solution-Oriented
Exploration, Data Engineering, Storytelling
