Introduction to Machine Learning in Geosciences

About

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 Geosciences. Datasets in Geosciences applications are 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 data processing techniques in geosciences.

This is an introductory-level course of Machine Learning. The aim of this course is to provide an overview of the main machine learning methods and their application to geophysical, geochemical, geological and environmental data.

The Summer School will be held on campus, in Pisa, at Dipartimento di Scienze della Terra, via Santa Maria, 53.

The program will be activated also in distance learning mode (TEAMS platform).

Course leader

Prof. Francesco Grigoli

Target group

Graduate Students, Early-Stage Researchers, Professionals.

Course aim

This course introduces students to the exciting world of machine learning (ML) with a specific focus on geosciences. By the end of this course, students will understand basic ML concepts and apply them to geoscience problems such as seismological data analysis, geochemical data analysis, climate modeling, and satellite images classification.

Fee info