Mauro Pelucchi is a senior data scientist and big data engineer responsible for the design of the "Real-Time Labour Market Information System on Skill Requirements" for CEDEFOP. He currently works as Head of Global Data Science @ EMSI Burning-Glass with the goal to develop innovative models, methods and deployments of labour market data and other data to meet customer requirements and prototype new potential solutions. His main tasks are related to advanced machine learning modelling, labour market analyses, and the design of big data pipelines to process large datasets of online job vacancies.
In collaboration with the University of Milano-Bicocca, he took part in many research projects related to the labour market intelligence systems.
He collaborates with the University of Milano-Bicocca as a lecturer at the Master Business Intelligence and Big Data Analytics and with the University of Bergamo as a lecturer in Computer Engineering.
Anglický jazykMauro Pelucchi
This tutorial shows how apply Regression Models and Deep Learning Models to
nowcasting stock markets crisis events.
Specifically, we'll how the transmission mechanisms across stock markets can
be used to train machine learning models to predict crisis events. The tutorial'll show
the entire pipeline: from the preparation of the dataset,
how balance observations and how measure our performances.