MATLAB for the WiDS Datathon: Predicting Timely Diagnosis of Metastatic Breast Cancer
About This Video
This workshop is designed to equip attendees with all the skills necessary to compete in the WiDS Datathon. Using the challenge dataset, we will show how you can import and work with tabular data, explore the relationships between different variables in the dataset, and process the data to make a cleaner, more helpful dataset. We will then walk through the process of quickly building and testing machine learning models for the challenge. By the end of this workshop, participants should have everything they need to create their own algorithms to accurately predict whether a patient with metastatic breast cancer was properly diagnosed within 90 days.
In This Video
Student Competitions Technical Evangelist- Data Science, Mathworks
Grace Woolson graduated from Hamilton College with a degree in computer science and a double minor in music and theatre, then joined MathWorks shortly after in 2021.
Grace is a Student Competitions Technical Evangelist at MathWorks, providing technical resources to students who participate in data science competitions and creating tutorials on how to use MATLAB for data science workflows. If you participated in the WiDS Datathon, you may recognize her as the author of the MATLAB tutorial provided for competitors. She has a passion for making the world a better place for all and believes artificial intelligence can be a great tool for this mission.