Code
IGFE CSC 7224
Semester
Fall
Domain
Informatique
Program
Master
Language
Anglais/English
ECTS Credits
4
Class hours
40
Workload
40
Program Manager(s)
Department
- Réseaux et Services de Télécom
Educational team
Organisation
Cours/TD/TP/projet/examen :Learning objectives
Understanding the main machine learning methods and algorithms
- Being able to apply them to computer networks and applications to solve practical use-cases
- Being able to define and follow a correct protocol (data pre-processing, training, test, validation) and to adapt it to the different use-cases
- Being able to use the main Python libraries for Machine Learning
Prerequisites
Basic Linear Algebra
Content
- Introduction (supervised / unsupervised Machine Learning, protocol, data preparation in python), Data exploration
- Linear Regression, Polynomial Regression, Evaluation of regression models, Regularization
- Classification
- Neural Networks (application to network intrusion classification)
- Random Forests and Ensamble Learning
- Unsupervised Learning and Anomaly detection (application to intrusion detection)
- Machine Learning for High-Speed Networking
- Predictive Maintenance
- Dimensionality Reduction
- Introduction to Reinforcement Learning
- Explainable Machine Learning
- Project presentation
- Theoretical exam
Evaluation
50% Theoretic exam
40% data science project
10% presence and participation