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.
This activity will start with two webinars on Machine Learning methods applied to different fields within the Earth System Sciences. In the first one, Dr. Marlene Kretchmer talked about her work with Machine Learning in Climate Sciences.
The second webinar will be on July 29th at 1pm UTC. Dr Jing Gao will talk about a creative application of machine learning for simulating global spatiotemporal patterns of urban land expansion over the 21st century.