WiDS Datathon Resources
Tutorials, sample code, videos, and event recordings will be posted here throughout the competition. Please see the WiDS Datathon 2022 resources page on Kaggle for additional resources and links.
WiDS Datathon 2022 Webinar: Data Science and Climate Change
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In this panel discussion, we speak with experts in a wide range of domains and institutions in order to explore the multi-faceted challenges posed by climate change. Not only do we aim to glimpse at how climate change impacts sectors spanning healthcare, energy and environmental protection, we will hear from our panel how data science can help us understand and mitigate the effects of climate change. This webinar is appropriate for audiences of all backgrounds – no prior familiarity with data science is assumed.
Watch the video |
WiDS Datathon 2022 Welcome Event Recording
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Learn about how to participate in this year’s WiDS Datathon! The WiDS Datathon 2022, organized by the WiDS Worldwide team, Stanford University, Harvard University IACS, and the WiDS Datathon Committee, will address an important way to mitigate the effects of climate change with a focus on energy efficiency. You’ll learn about the dataset and challenge, how to participate on Kaggle, datathon tutorials and resources, and upcoming datathon workshops.
Watch the video | Link to presentation |
GM Tutorial: A Data Scientist's Perspective
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GM Data Scientist Viritha Kaza discusses the analytics value-complexity curve, job opportunities in data science and walks through a sandboxed dataset tutorial in a Jupyter Notebook. At ~11 minutes, she shows techniques on how to mine the data for different insights, applicable to solving the WiDS Datathon 2022 challenge.
Watch the tutorial |
CCAI Tutorial: Building Load Forecasting
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by Marcus Voss and Nikola Milojevic-Dupont, Climate Change AI
We will investigate the task of building load forecasting and will try to gain domain knowledge about building energy prediction of relevance to the WiDS Datathon 2022. The task of building load forecasting involves predicting hourly energy use 24h ahead by learning the relationship between historical load data and predictive features. It is similar to the task of the WiDS Datathon 2022 in the sense that in both tasks we are aiming to predict future energy use based on predictive features. Read the tutorial |
Building Regression Models: A Tutorial for the WiDS Datathon 2022
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by Grace Woolson, Application Support Engineer
Mathworks is excited to support the WiDS Datathon by providing complimentary MATLAB Licenses, tutorials, and resources to each participant. This tutorial will walk you through the steps of solving a regression problem with MATLAB for any dataset, while showing examples for each step using a sample dataset. Read the tutorial or Watch the video |
A Beginner’s Tutorial for the WiDS Datathon 2022 challenge
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by Sharada Kalanidhi, Co-Chair of the WiDS Datathon Committee
Sharada Kalanidhi, Data Scientist at the Stanford Med School, walks us through a beginner’s tutorial on the WiDS Datathon. She discusses alternate approaches to modeling the data. Read the tutorial |
Getting Started with Kaggle - WiDS 2022 Datathon Videos
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by Usha Rengaraju, Kaggle 2x Grandmaster
Video: Getting Started with Kaggle - an introduction on how to get started with Kaggle and how to navigate WiDS Datathon Kaggle competition page Video: Energy Consumption Prediction - a baseline notebook walkthrough of WiDS 2022 Datathon |