This course is an introduction to Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) applied to Earth observation data. The aim of the course is to provide an overview of machine learning potential for EUMETSAT data and the main machine learning techniques, with hands-on modules using real world data. The course is composed of different modules, addressing both theory and practical examples.
The course covered:
- A brief introduction to AI history
- The main branches of machine learning: Supervised and Unsupervised Learning
- Theory on the main algorithms used on supervised/unsupervised learning
- Theory on Deep Learning (Multi layer perceptrons and CNN)
- Existing open source tools
- How to build AI workflows
- Hands on: classification, regression, clustering and image classification tasks.
