{"id":45540,"date":"2025-04-30T14:17:42","date_gmt":"2025-04-30T19:17:42","guid":{"rendered":"https:\/\/uwm.edu\/libraries\/?page_id=45540"},"modified":"2026-03-23T14:24:00","modified_gmt":"2026-03-23T19:24:00","slug":"text-analysis-with-python","status":"publish","type":"page","link":"https:\/\/uwm.edu\/libraries\/digital-humanities\/dh-lab-resources\/text-analysis-with-python\/","title":{"rendered":"Text Analysis with Python"},"content":{"rendered":"\n
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Text Analysis with Python <\/h2>\n\n\n\n

Text Analysis for the Humanities<\/strong>\u00a0Workshop<\/strong>
Asynchronous Lesson Modules<\/a>
Instructors: Karl Holten, Stephen Appel, Jie Chen, Stephanie Surach, Ann Hanlon<\/p>\n\n\n\n

We have created learn-on-your-own lesson modules for this recently developed Carpentries workshop, a practical Introduction to Text Analysis, designed for those with Python experience (how to create functions, for loops, conditional logic, use the pandas library, etc.). Check out our\u00a0Intro to Python<\/strong>\u00a0workshop<\/a> videos, if you need an introduction. The workshop covers Natural Language Processing (NLP) basics, API usage, data preparation, document\/word embeddings, topic modeling, Word2Vec, Transformer models using Hugging Face, and ethical considerations. Students and researchers working in the digital humanities are especially encouraged to check this out! View the\u00a0the lesson homepage<\/a>\u00a0for an overview of the topics covered.<\/p>\n\n\n\n

This is a pilot workshop<\/strong>, testing out a lesson that is still under development. We are also experimenting with a new delivery method by offering this as a series of asynchronous modules. The lesson authors would appreciate any feedback you can give them about the lesson content and suggestions for how it could be further improved.<\/p>\n\n\n\n

Online course videos and lessons: https:\/\/guides.library.uwm.edu\/carpentries\/TAP<\/a><\/strong><\/p>\n<\/div>\n\n\n\n