Introduction to Machine Learning for Earth Observation - A practical approach

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EUMETSAT

Tue, Sep 27 - Thu, Sep 29 2022

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 will cover:

  • the main branches of machine learning: Supervised and Unsupervised Learning.
  • Deep Learning.
  • Existing open source tools.
  • How to build AI workflows.
  • Hands on: classification, regression, clustering and image classification tasks.

At the end of the course you will be able to:

  • understand how to address your problem using machine learning techniques;
  • create you own workflow based on the templates provided in the course;
  • find tools from the various existing libraries;
  • appreciate the limitations of you knowledge and where to find expert knowledge.

 

Member State weather and associated services starting to work in AI/ML on weather data.

Darmstadt