Learning

TaiESM1 Model Simulation

I obtained skills of conducting sumulations, including change of enreainment rate, volcanic eruption and quadruple carbon dioxide, from AMIP to coupled runs.

Machine Learning

Embarking on a new frontier, my upcoming project delves into the fascinating realm of machine learning. I participated in foundational class called Machine Learning in Atmospheric Thermodynamics at National Taiwan University from Sepember 2022 to January 2023, gaining hands-on experience in training supervised models through Pytorch to discern atmospheric profile inversions (my codes). Building on this foundation, my focus is now shifting towards exploring the realm of unsupervised machine learning in tropical meteorology.

I also participated in Machine Learning in Weather & Climate, a MOOC class up to 40 hours organised by the European Centre for Medium-Range Weather Forecasts in partnership with the international Foundation Big Data and Artificial Intelligence for Human Development.

Page updated

Google Sites

Report abuse