Descriptif
Data streams are everywhere, from F1 racing over electricity
networks to social media feeds. Data stream mining or Real-Time
Analytics relies on and develops new incremental algorithms that
process streams under strict resource limitations. This course focuses
on, as well as extends the methods implemented in open source tools as
MOA and Apache SAMOA. Students will learn to how select and apply an
appropriate method for a given data stream problem; they will learn
how to design and implement such algorithms; and they will learn how
to evaluate and compare different solutions.
Programme to be followed
1. Introduction
2. Stream Algorithmics
3. Concept Drift
4. Classification
5. Ensemble Methods
6. Clustering
7. Frequent Pattern Methods
Diplôme(s) concerné(s)
Parcours de rattachement
Format des notes
Numérique sur 20Littérale/grade européenPour les étudiants du diplôme Diplôme d'ingénieur
L'UE est acquise si Note finale >= 10- Crédits ECTS acquis : 3 ECTS
- Crédit d'UE électives acquis : 3
La note obtenue rentre dans le calcul de votre GPA.