Nelson has a Bachelor's degree from Northwestern University and a Master's degree from University of California, Berkeley in Mechanical Engineering. His graduate work specialized in developing and applying new Computational Fluid Dynamic algorithms to astrophysical fluid dynamic problems to study protoplanetary disk and star formation. At the tail end of his graduate school career, he attended a data science workshop hosted by University of California, Berkeley's data science center where he participated (in a team of 4) in State Farm's distracted driver Kaggle competition and developed a strong interest in machine learning and its large potential to solve new problems. Since then, he has dived head first into learning the tools and skills at NYC Data Science Academy needed to be a professional data scientist.
Introduction Kaggle competitions are a good place to leverage machine learning in answering a real-world industry-related question. A Kaggle competition consists of open questions presented by […]
Introduction In 2008, I was a senior in high school applying to colleges around the country, eager to start the next phase of my life. Unfortunately, […]
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