Former teaching material

This is a part of the teaching material I created when I was associate professor (maître de conférences, HDR) at INSA de Lyon and the LIRIS laboratory from 2005 to the end of 2021.

Cours+TD+TP Deep Learning and Differentiable Programming (IF - 5ème année)

  • Part 1 - Introduction
    • 1.1: Introduction: machine learning, a couple of applications [36 slides]
    • 1.2: A short history of deep learning [8 slides]
    • 1.3: An extremely short crash course on fitting and generalization [16 slides]
  • Part 2 - Neural Networks and PyTorch
  • Part 3 - Scaling up: computer vision, transfer learning, visualization
  • Part 4 - Structure: sequences, graphs, attention
  • Part 5 - Advanced applications
  • Part 6 - A gentle introduction into learning theory
    • 5.1: A gentle introduction into learning theory [45 slides]
    • 5.2: A concrete application of the usage of learning theory in DL [35 slides]

    PyTorch sources:
    The full PyTorch sources of the slides are here.
    Pratical Excercise session:
    (will be held by Edward Beeching, web site will be published shortly.)

    Neural models in python for object detection and future forecasting.
    [Project page]

TD Advanced algorithms and data structures for Artificial Intelligence (IF - 3ème année)

With Christine Solnon: Shortest path problems, topological orderings of graphs, minimum spanning trees, the travelling saleman problem etc.

Cours+TD+TP Computer Architecture / Architectures d'ordinateurs (IF - 3ème année)

  • Session 1: Instruction Set Architecture, assembler (1) [PDF]
  • Session 2: Instruction Set Architecture, assembler (2) [PDF]
  • Session 3: Building a RISC processor from scratch. Instruction level parallelism [PDF]
  • Session 4: Super-scalar processors, multi-threading, multi-core; ARM vs. x86 [PDF]
  • Session 5: Memory hierarchy : cache, virtual memory [PDF]
  • Session 6: Massively parallel processors (GPUs) [PDF]
  • Full content on Moodle (in French)

Cours Robotique et vision par ordinateur OT (Option transversale 5A) "Robotique")

  • Vision for mobile robotics
  • Visual SLAM with Kinect
  • Object and face detection : deep learning
  • Human-robot interaction : pose estimation
  • Human-robot interaction : gesture recognition
  • Human-robot interaction : face-to-face interaction
  • The slides [PDF]

Cours+TD+TP Lanières SCAN et L - Groupes 72,54 (PC - 2ème année)