Python: Introduction to Machine Learning for Text Classification
Machine Learning (ML) has transformative applications across government, healthcare, education, marketing, business, and life sciences. By employing machine learning techniques, computers can learn from past data and make predictions about new data.
This course guides participants through building their own text-based Machine Learning models. As applications, we focus on Text Clustering and Classification—fundamental techniques for organizing and categorizing text data. These core skills form the foundation for advanced applications including content analysis, sentiment analysis and document organization.
Through hands-on exercises using IPython notebooks, participants will learn to apply ML techniques to real-world text data, understand when different approaches work best, and avoid common pitfalls in ML projects.
This course is offered in collaboration with the Linguistic Research Infrastructure (LiRI) at UZH.
| Code: | HS26-APTC-01 |
|---|---|
| Language: | English |
| Term for application: | 30.08.2026 |
| Instructor: | Gerold Schneider |
| Further Instructor(s): |
Tannon Kew Tilia Ellendorff |
| Dates: |
Wed 02 September 2026
(09:00am - 12:00pm)
Fri 04 September 2026 (09:00am - 12:00pm) Wed 09 September 2026 (09:00am - 12:00pm) Fri 11 September 2026 (09:00am - 12:00pm) |
| Location and room: |
Universität Zürich Irchel, Winterthurerstrasse 190, 8057 Zürich Y01-F-49 Show on Google Maps |
| Occasion: | Further information about the offer. |
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