Paolo Cremonesi is associate professor at the Computer Science Department of Politecnico di Milano and local coordinator of the EIT Digital double degree programme in Data Science. His research interests include recommender systems, machine learning, predictive models, and high-performance computing.
Coursera
Dive into the world of recommender systems with our foundational course. Explore both collaborative filtering and content-based approaches, understand essential algorithms, and learn how to effectively use and evaluate these powerful tools in providing personalized recommendations. This course will equip you with a deep understanding of the benefits and limitations of different methods.
Coursera
Discover how to use cutting-edge machine learning methods to create powerful recommender systems in our Advanced Recommender Systems course. This course will guide you through the intricacies of building advanced models that leverage user data to provide personalized recommendations. Learn about hybrid approaches, factorization machines, and optimizing your system for improved accuracy.