Course taught in the Data and Knowledge 2nd year Master Program of Université Paris Saclay
The Internet of Things (IoT) is producing huge quantities of data in real-time as data streams. 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. 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.
Lecturers: Jesse Read and Albert Bifet
- 10% Lab Assignments
- 30% Project
- 60% Final Test
- 1. Introduction Slides
- 2. Stream Algorithmics Slides
- 3. Classification Slides
- 4. Concept Drift Slides
- 5. Evaluation Slides
- 6. Concept Drift and Sequential Data Slides
- 7. Ensembles Slides
- 8. Clustering Slides
Internships available here.