Starting Spring 2023 Tutorial Series – February 15

The Undergraduate Machine Learning Research (UMLR) Community of which the Informatics Skunkworks is a part will be hosting its first in a series of introductory machine learning tutorials next week! The 30 minute hands-on tutorial will give a quick introduction to machine learning and we’ll walk through together as a group an example of starting with a simple dataset and ending up with a trained and assessed machine learning model that predicts materials properties.

For more details and a list of upcoming tutorials see the informatics help desk web page


Speaker: Dr. Benjamin Afflerbach

Who: New or prospective machine learning researchers

What: An introduction to common steps in a research workflow to start with a new dataset and end up with a trained and assessed machine learning model. We’ll introduce ideas for data cleaning, featurization, a common first model to try (random forests), model assessment, optimization, and making predictions. The activity will use scikit-learn as the primary ML software package, and is entirely cloud based so you do not need to do any prep to install anything before or during the activity. If you’d like to preview the content or work through independently you can find the resource hosted on Nanohub at the link below.

When: February 15 at 10:00 am central time.

Where: In the normal help-desk Zoom call. We’ll create a breakout room for workshop specific attendees to separate out from general drop-in questions.