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: Maroua Bahri, George Hebrail, Mariam Barry, Jesse Read and Albert Bifet


  • 40% Lab Assignments
  • 60% Project

Lecture Slides

  1. Classification and Ensembles. Slides
  2. Big Data Stream Management
  3. Time series analytics
  4. Reinforcement Learning

Session Labs

  1. River Lab Source
  2. Lab Massive Online Analysis MOA Source


Projects: TBA


Book Machine Learning for Data Streams.