WiDS Datathon Resources

Tutorials, sample code, and other resources will be posted here throughout the competition

Getting Started with Kaggle - WiDS 2021 Datathon Videos

by Usha Rengaraju, Kaggle 2x Grandmaster
Video 1: Getting Started with Kaggle - an introduction on how to get started with Kaggle and how to navigate WiDS Datathon 2021 competition page
Video 2: Diabetes Prediction for ICU Patients - a baseline notebook walkthrough of WiDS Datathon 2021 challenge

MATLAB Benchmark Code for WiDS Datathon 2021

by Neha Goel, Technical Lead for AI/Data Science competitions at Mathworks
This dataset presents an opportunity to learn about the data modeling and processing challenges a real-world data problem brings. In this blog, I will talk about some basic methods to handle data challenges. To learn some more methods you can go through this Data Science Tutorial video series.
Read the tutorial

Deep Dive Discussion: A Data Scientist's Perspective on the WiDS Datathon

by Sharada Kalanidhi, WiDS Datathon Co-Chair
This dataset presents an opportunity to learn about interesting and real-world modeling challenges, and is different from other curated datasets in textbooks and classic machine learning exercises.  For that reason, I discuss some of the challenges you may experience around missing data, multicollinearity and linear/ nonlinear approaches. I will also provide resources to help you on these topics.
​Read the discussion

Lessons Learned + Best Practices with Health Data

This webinar on-demand features distinguished panelists that explore the challenges and opportunities of working with healthcare data, and discusses issues around the technology and the clinical aspect of healthcare machine learning. 
Watch the webinar