REGISTRATION NOTES
After clicking the registration link for your desired workshop, be sure to use your @berkeley.edu or @lbl.gov email address in the Zoom registration box to ensure a seamless process. Additionally, when joining the workshop, participants need to be logged in with their institutional email address in Zoom to be granted admission. You may need to log out and log back in.
Location: Remote via Zoom.
Recordings: This D-Lab workshop will be recorded and made available to UC Berkeley participants for a limited time. Your registration for the event indicates your consent to have any images, comments, and chat messages included as part of the video recording materials that are made available.
Date & Time: This workshop is a 2-part series running from 1pm-3pm each day:
• Part 1: Mon Oct 14
• Part 2: Wed Oct 16
Start Time: D-Lab workshops start 10 minutes after the scheduled start time (“Berkeley Time”). We will admit all participants from the waiting room at that time.
Description
This two-part workshop provides an introduction to machine learning algorithms using the tidymodels package. It covers what machine learning is, which problems it is most and least equipped to address, and explores the tidymodels framework to fit supervised machine learning models in R.
Addressing machine learning problems requires a deep conceptual understanding of the material. While the workshop will cover coding in R, it will also dedicate a significant portion of the time to motivating machine learning techniques.
By the end of the workshop, learners should feel prepared to explore machine learning approaches for their own data problems. This workshop does not cover unsupervised machine learning techniques.
Prerequisites: Familiarity with R programming and data wrangling is assumed. If you are not familiar with the materials in Data Wrangling and Manipulation in R, we recommend attending that workshop first. In addition, this workshop focuses on how to implement machine-learning approaches. Learners will likely benefit from previous exposure to statistics.
Workshop Materials: https://github.com/dlab-berkeley/R-Machine-Learning
Software Requirements: Installation Instructions for getting started with using R and RStudio.
Feedback: After completing the workshop, please provide us feedback using this form
Questions? Email: dlab-frontdesk@berkeley.edu