Scope: Machine learning plays an increasingly important role in many scientific areas, including geo-information science and remote sensing, ecology, biosystems engineering, and bioinformatics. Today, scientific data are growing in complexity, size, and resolution, and scientists are challenged to leverage available data to inform decision making. In this course, you will learn how to model patterns and structures contained in data, and evaluate data-driven models, i.e. models that learn directly from observations the phenomena under study.
Target group: The course is aimed at PhD candidates, postdocs, and other academics that are interested in machine learning applied to environmental data
Course duration: 5 days
Contact: PE&RC Office: office.pe@wur.nl
Registration of interest: You can register your interest HERE (note: this is not an official registration).
