🗓️ June 26, 2025
🕘 9:00 AM – 4:00 PM
📍 University of Kassel
Overview:
The abundance of text data and the emergence of powerful deep learning models have rapidly advanced Natural Language Processing (NLP). However, tailoring models to specific tasks still demands human-annotated data, which can be time-consuming. Active Learning strategically involves humans in the learning loop, selecting instances for annotation to maximize performance gains. This approach optimizes human effort and enhances the model’s adaptability, making training more efficient.
Join us in Kassel for a free full-day workshop on Human-in-the-Loop and (Deep) Active Learning. Through hands-on exercises, you will learn to design a (Deep) Active Learning Cycle using Python.
Requirements:
- Basic Python Skills
- Basic experience in Machine Learning/Deep Learning
- Bringing your own laptop to the workshop
Application deadline: May 14, 2025
More information: https://www.berd-nfdi.de/berd-academy/active-learning-2025/
For inquiries, please contact: berd-academy@stat.uni-muenchen.de