Workshop Announcement. Registration is now open.
Deep Learning with Humans-In-The-Loop: Active Learning for NLP
With Lukas Rauch
๐๏ธ July 4th, 2024
๐ 9:00 AM – 4:00 PM
๐ 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 modelโs adaptability, making training more efficient.
What to Expect:
In this full-day workshop, participants will delve into the fundamentals of Human-In-The-Loop Learning and (Deep) Active Learning. Through hands-on exercises, attendees will learn to design a (Deep) Active Learning Cycle using Python.
Requirements:
- Basic proficiency in Python
- Fundamental knowledge of Machine Learning/Deep Learning
- Bring your own laptop to fully engage in the workshop activities
About the Instructor:
Lukas Rauch is a researcher within the AI for Computationally Intelligent Systems (AI4CIS) team at the University of Kassel, Germany. His expertise spans (Deep) Active Learning and Optimization.
More information and registration: https://dev.berd-nfdi.de/berd-academy/active-learning-2024/
For inquiries, please contact: berd-academy@stat.uni-muenchen.de