Machine Learning - Learning Groups

This is a Machine Learning initiative that I am leading. Anyone interested is welcome to apply!

There is a growing interest in Machine Learning (ML) methods applied to Earth System science. Together with more traditional machine learning methods like classification and regression methods, new techniques like artificial neural networks or causal discovery algorithms are showing to have great potential to solve challenges in our field. Learning to apply these methods would be beneficial for Early Career Researchers (ECRs), this is why YESS is organizing a learning activity to bring together members of our community who want to apply these methods to their own data and problems.

There is a huge amount of resources available online, workshops, open source software, codes and datasets and it can be hard to know where to start. These learning groups are intended to provide ECRs the opportunity of engaging in a guided and collaborative learning process via the participation in small learning groups. Additionally, we expect these groups to allow discussion on the interpretation of the results and the combination of ML methods with physics-based methods.

The objectives of the learning group activities can be summarized to:

  1. Learning machine learning fundamentals;
  2. Learning how to pre-process environmental science data to apply machine learning (ML) methods;
  3. Build and train a ML (or deep learning) model;
  4. Evaluate and discuss model predictions and physical interpretation of the ML models with colleagues; and
  5. Solidify understanding of the above topics through group discussion in a closing session.

To apply or learn more about this initative check out this link