Machine learning in fluid dynamics
Experimental and numerical fluid mechanics investigations generate enormous amounts of data. The datasets are often extremely complex and their analysis is challenging. As a result, valuable information present in the data often remains undiscovered and unused. Machine learning (ML) makes it possible to algorithmically extract and use patterns from the data, making it a valuable analysis and modeling tool for fluid mechanics data. Through this course, students have the opportunity to develop an intuitive understanding of commonly used ML algorithms, apply them to research-grade datasets, and embed the trained ML models in simulation tools.
