Over the years, machine learning has become increasingly popular among researchers, offering innovative solutions to challenges like image classification, individual tracking, and  behavior prediction. The aim of this workshop to introduce participants to the world of machine learning and computer vision in an accessible manner. This workshop is specifically tailored for biologists and will focus on practical applications for biology PhD students and researchers, covering three key areas: image classification, object detection/tracking, and pose estimation.

Regardless of your research subject within the field of Biology, (animals, plants, cells,...) this workshop will be useful and applicable to all topics. 

Throughout the workshop, you will gain an intuitive understanding of the fundamentals of image processing and supervised machine learning. Moreover, you will actively engage in hands-on lab sessions, where you will have the opportunity to directly apply the acquired concepts through practical exercises.

Learning outcomes

By the end of the workshop, you should be able to:

- Gain insights into digital images and how machines can learn from them.

- Learn to train and evaluate different kinds of machine learning models.

- Feel confident in applying machine learning techniques to your own research projects.

Requirements

No prior knowledge of machine learning is required, but some basic familiarity with Python is recommended.

Participants should bring their own laptops.