Training

Christian Lessig, Team lead for ML modelling at ECMWF, unpacks self-supervised learning exploring why it has become...

Mario Santa Cruz explains the core principals of Graph Neural Networks (GNN), the different kinds of GNNs and its...

Maria Luisa Taccari introduces convolutional neural networks, explaining why they are more efficient than standard...

Peter Dueben, Head of Earth System Modelling at ECMWF, explores how machine learning is revolutionising weather and...

Jesper Dramsch will cover a final important aspect in Machine learning, training the models and hyperparameter tuning to...

Jesper Dramsch will cover the most important building blocks in deep-learning, such as different types of neural...

In this video Jesper highlights five important architectural networks useful for weather and climate models and their...

Jesper Dramsch will give a brief introduction to deep learning neural networks and why it is an important technology for...

William Becker from ECMWF will describe tree-based Machine learning models, an approach type that is not based on neural...

William Becker, a data scientist working in developing training courses in machine learning at ECMWF provides a summary...

This video is the recording of the panel discussion on 'The Future of Earth-System Modeling in the Era of Artificial...

Matthew Chantry, Strategic Lead for Machine Learning at ECMWF, introduces the Anemoi framework – an open-source, end-to...