Previously, the game preparation process for UIUC football coaches was manual and it took hours to get ready.
In this tech talk, we’ll discuss how the data scientists from Amazon ML Solutions Lab selected important features and used XGBoost in Amazon SageMaker to help football coaches to gain insights and prepare games better. We’ll discuss the methodology we used in details and provide code examples of model training in Amazon SageMaker.
This model is customized for UIUC’s football team and their opponents, and will help UIUC’s coaches prepare for more scenarios in upcoming seasons. Additionally, it will help players react correctly and quickly to game situations.
Daliana&Ninad (Amazon)
Daliana Zhen LiuSenior Data Scientist at the Amazon ML Solutions Lab. She builds AI/ML solutions to help customers across various industries to accelerate their business. Previously, she worked at Amazon’s A/B testing platform helping retail teams make better data-driven decisions
Ninad Kulkarni
Data Scientist in the Amazon Machine Learning Solutions Lab. He helps customers adopt ML and AI by building solutions to address their business problems. Most recently, he has built predictive models for sports and automotive customers
Tianyu Zhang
Data Scientist in the Amazon Machine Learning Solutions Lab. He helps customers solve business problems by applying ML and AI techniques. Most recently, he has built NLP model and predictive model for procurement and sports
Jan 20, 10:00 AM PST 
