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Dettaglio Insegnamento

Contesto
Anno Accademico 2021/2022
Corso di Studi Dott. - MI (1380) Ingegneria dell'Informazione / Information Technology
Anno di Corso 1

Scheda Insegnamento
Codice Identificativo 057368
Denominazione Insegnamento MACHINE LEARNING METHODS FOR COMMUNICATION NETWORKS AND SYSTEMS
Tipo Insegnamento MONODISCIPLINARE
Crediti Formativi Universitari (CFU) 5.0
Programma sintetico The amount of information which nowadays we can retrieve from communication networks and systems is extremely high (e.g., users behavior, traffic samples, network alarms, signal quality indicators, etc.). However, the variability and dynamicity of these indicators are such that exploiting this information in a proper manner is not always straightforward when adopting models traditionally utilized for network design, operation and reconfiguration. The course aims at providing fundamentals of Machine Learning (ML) techniques which can be suitable for communication networks and systems and gives an overview of the typical research problems tackled with such methods. Lectures will be structured into two main parts. In the first part, basic concepts of Machine Learning will be discussed, including the following: - Supervised Learning (Regression and Classification, Linear regression, Logistic regression, Artificial Neural Networks, Support Vector Machines) - Unsupervised Learning (Clustering algorithms, K-means, EM algorithm) In the second part of the course, applications of ML techniques to communication networks and systems problems will be discussed. Among the main problems which will be treated there are (list is non-exhaustive): - Traffic prediction - Traffic pattern extraction - BER prediction - Network anomaly detection - Quality of Transmission estimation - Failure detection, localization and cause identification - EDFA power excursion minimization
Settori Scientifico Disciplinari (SSD)
Codice SSD Descrizione SSD CFU
ING-INF/03 TELECOMUNICAZIONI 5.0

Dettaglio
Scaglione Docente Programma dettagliato
Da (compreso) A (escluso)
A ZZZZ Musumeci Francesco
manifestidott v. 1.7.0 / 1.7.0
Area Servizi ICT
12/08/2022