Attendees will receive a concise overview of the fundamental principles of deep learning and its broad applications. Additionally, the workshop will briefly guide participants through the process of employing deep learning models, from collecting training datasets to model training and performance evaluation when addressing real-world challenges faced by researchers working with large animal based datasets. This is an introductory workshop designed for students and researchers who have not yet applied deep learning methods to their data.

The workshop is organized within the DEEPWEAVER project (“Deep Learning meets Behavioural Ecology in the wild: methodological applications using the sociable weaver – 101183160”), part of the Marie Skłodowska-Curie Actions – Staff Exchanges programme funded by the European Union.

Duration: 3 hours (presential)
Max. participants: 20
Info and Requirements: Basic knowledge of R coding, Python or other programming language is desired. Attendants need to bring their own laptops.

André Ferreira is an evolutionary biologist and a postdoc researcher at the University of Zurich, and Liliana Silva is a research technician at BIOPOLIS. Their research primarily focuses on using artificial intelligence, particularly deep learning, to automate the collection of behavioural data in the wild, with a particular emphasis on birds.