ECTS
3 credits
Component
UFR PhITEM (physique, ingénierie, terre, environnement, mécanique)
Semester
Printemps
Description
The objective of this course is to understand the principles and the application of machine learning methods (one of the branches of artificial intelligence) in the context of geosciences. To do so, we will introduce the concepts, the main uses in geosciences (detection/understanding of natural phenomena from satellite imagery, time series, etc.), the main problems addressed (regression, classification and unsupervised learning) as well as the main methods (random forests, PCA..). Finally, we will briefly introduce deep learning methods.
The main goal of this course is to know how to use these tools by oneself, to understand the main problems, but also to understand their limits. For this, the module is based on 12 hours of practical work in Python.
Pre-requisites:
Basic knowledge of Python programming and mathematics.
Languages: English, French
Course parts
- UE Introduction to Machine learning in Earth Sciences - CM/TDLectures (CM) & Teaching Unit (UE)12h
- TPPractical work (TP)12h