Deep Learning for Mobility
The module is a practical introduction to machine learning with focus on Deep Learning (DL). The first part of this course introduces the methodological aspects of Deep Learning, and discusses the features, advantages and disadvantages of different DL solutions. The second path of this course includes a hands-on session discussing best practices for a successful DL workflow development on a real-world example of mobility analysis. During the hands-on session, participants will learn how to exploit some of the most popular and powerful libraries, such as scikit-learn and Keras.
Course background knowledge:
Necessary background includes undergraduate level knowledge on Python programming, basic knowledge on ML tasks classification, regression and clustering.
Tutors
Franco Maria Nardini
CNR - National Research Council of Italy
Franco Maria Nardini is a senior researcher with ISTI-CNR in Pisa (Italy). He received the Ph.D. in Information Engineering from the University of Pisa in 2011. His research interests are focused on Web Information Retrieval (IR), Machine Learning (ML), and Data Mining (DM). He authored more than 70 papers in peer-reviewed international journal, conferences and other venues. In the past, he has been Tutorial Co-Chair of ACM WSDM 2021, Demo Papers Co-Chair of ECIR 2021, Program Committee Chair of the Italian Information Retrieval Workshop (IIR) in 2016 and General Chair of the International Workshop on Tourism Facilities (co-located with IEEE/WIC/ACM Web Intelligence) in 2012. He is co-recipient of the ACM SIGIR 2015 Best Paper Award, of the ECIR 2022 Industry Impact Award, and of the ECIR 2014 Best Demo Paper Award. He is member of the program committee of several top-level conferences in IR, ML and DM, like ACM SIGIR, ECIR, ACM SIGKDD, ACM CIKM, ACM WSDM, IJCAI, ECML-PKDD.
Salvatore Trani
CNR - National Research Council of Italy
Salvatore Trani is a researcher at the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR), working with the High Performance Computing (HPC) Lab. He received the Ph.D. in Computer Science from the University of Pisa in 2017. His research interests focus on Web Information Retrieval (IR), Machine/Deep Learning (ML) and Data Mining (DM). He authored more than 20 papers in peer-reviewed international journals, conferences, and other venues. He is also a member of the program committee of several top-level conferences in IR, ML and DM, like ACM SIGIR, ACM SIGKDD, ACM CIKM, ACM WSDM, ACM WWW. He is co-recipient of the ACM Symposium on Document Engineering Best Student Paper Award in 2016, and of the ECIR 2022 Industry Impact Award.