This three-part workshop series (5/23, 5/25/ 5/27) introduces participants to natural language processing (NLP) with Python. It builds on our text mining series, “GettingStarted with Textual Data,” by extending the scope of data-inflected text analysis to include various methods of modeling meaning. Sessions will cover NLP topics ranging from segmentation and dependency parsing to sentiment analysis and context-sensitive modeling. We will also discuss how to implement such methods for tasks like classification. Basic familiarity with analyzing textual data in Python is required. We welcome students, postdocs, faculty, and staff from a variety of research domains, ranging from health informatics to the humanities.

Workshop series dates are May 23, May 25, and May 27, 2022, 10:00 AM – 12:00 PM.

Prerequisites: Instructors will distribute a zipped directory of notebooks and files the week prior to the workshop. Participants are required to load this data into their Google Drive account before our first session.
In addition to this prep work, a basic knowledge of working with textual data in Python is required. Specifically, participants should attend DataLab’s 3-part “GettingStarted Working with Textual Data” workshop series and be able to do the following with Python:
Load text data into Python
Perform basic text cleaning actions
Generate data structures like document-term matrices
Conduct preliminary counting processes on corpora

Software: Python; Google Colab (instructors will provide notebooks and data).
Location: Zoom.
APPLY to workshop: registration.genomecenter.ucdavis.edu…
 
Sponsored by DataLab.