Environmental datasets often contain numerous parameters. Multivariate statistics allow us to simultaneously explore, understand and model such datasets. This course provides conceptual introduction and guidelines for applying multivariate statistical tool ...
Hands-on introduction to data science and machine learning. We explore recommender systems, generative AI, chatbots, graphs, as well as regression, classification, clustering, dimensionality reduction, text analytics, neural networks. The course consists o ...
The course aims to introduce the basic concepts and results on metric embeddings, or more precisely on approximate embeddings. This area has been under rapid development since the 90's and it has strong impact on algorithms for discrete optimization proble ...
This class provides a hands-on introduction to data science and machine learning topics, exploring areas such as data acquisition and cleaning, regression, classification, clustering, neural networks, and visualization. The course consists of lectures and ...
Introduction to multivariate data analysis and modelling. The course helps for a critical choice of methods and their integration in a research planning. It prepares for complexe data analysis in various fields of environemental sciences. Use of dedicated ...