This workshop will introduce document classification and sentiment analysis using Python and Scikit-Learn. Participants will learn how to build, train, and evaluate a custom supervised machine learning classifier to predict the topic and sentiment of text documents. 

NOTE: This event is available to all University of California and California State University affiliates and research partners. Please register using your university email address if you have one. 

This workshop will be offered online through UCSF Zoom and in person at the UCSF FAMRI Library at Mission Bay. All registrants will receive an email from libcal with location information and a Zoom link prior to the start of the workshop. You will have the option to attend in person or online regardless of how you register, so please select the option you think is most likely at the time of registration. 

About the series
Data and Document Analysis with Python, SQL, and AI is designed for UCSF researchers and analysts interested in learning Python for Data Analysis, with an emphasis on text analysis and UCSF library collections. Each session will involve short mini lectures, interspersed with hands-on exercises.

About the instructor
Geoffrey Boushey is a Data Science Specialist at the UCSF Library. Geoff provides data analysis workshops and consulting sessions for the research community, with an emphasis on AI tools to extract, transcribe, annotate, and analyze data from digital audio, video, and image media. Geoff holds undergraduate degrees in Mathematics and English Literature and an M.S. in Industrial Engineering and Operations Research. 

Accessibility statement
UCSF welcomes all participants to our events. If you need a reasonable accommodation to participate in this event because of a disability, please contact Geoffrey Boushey at geoffrey.boushey@ucsf.edu as soon as possible.