Synopsis of the course:
A large number of applications that only a few years ago would have been considered impossible to be performed without any sort of human interaction are now autonomously executed by increasingly more powerful machines and sophisticated algorithms. Fed by an enormous quantity of available data, machine learning algorithms can learn, without being explicitly programmed, to solve complex tasks such as speech, face, and object recognition or to play and even defeat the best human players at the ancient game of Go.

Machine-learning is becoming an essential skill in many data-intensive scientific fields, including Geophysics. Geophysical datasets are in fact growing in size and variety at an exceptionally fast rate, highlighting the need for new data processing and assimilation techniques that are able to exploit the information deriving from this data explosion. In this framework, Machine-learning techniques have the potential to push forward the state of the art of geophysical data processing techniques.

The aim of this course is to provide an overview of the main machine learning methods and their application to geophysical, geological and environmental data.