This workshop will introduce topic modeling, a common natural language processing technique used to identify topics within a collection of documents. Participants will use Python, scikit-learn and Gensim to identify hidden patterns and topic clusters within a series of wide-ranging documents. 

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.