Teaching

Bachelor Courses

  • Architecture des ordinateurs I
  • Interfaces Homme-Machine (IHM, 2017)
  • Machine Intelligence (2008 & 2010)
  • Machine Learning (MLG 2018)
    • 01. Introduction
      • Lab1: Introduction to Python notebooks (zip, pdf)
    • 02. Artificial Neural Networks
      • Lab2: Perceptrons, MLPs and Backpropagation
    • 03. Artificial Neural Networks II
      • Lab3: Crossvalidation
    • 04. Feature extraction
    • 05. Feature construction
      • Lab4: Model selection
      • Lab5: Speaker recognition (delay for report: < X.4.2018, 23h59)
    • 06. Deep Learning
      • Lab6: CNNs
    • 07. Unsupervised learning
      • LabSOM_Part1.zip
    • 08. Self-Organizing Map Applications
      • LabSOM_Part2.zip (delay for report: < X.5.2018, 23h59)
    • 09. Genetic Algorithms
      • GAlab1: design with a purpose
      • GAlab2: a tool for optimization (delay for report < X.6.2018, 23h59)
    • 10. Reinforcement Learning
      • Introductory chapter (PDF)
    • 11. Swarm Intelligence
  • MAGICIEL:MAtériel et LoGICIEL des ordinateurs (MAG, 2004-2014)
  • Science-fiction et technologie (SFI, 2015)
  • Systèmes bio-inspirés (SBI, 2005-2015)

Master Courses