MLRF official web page

J. Chazalon

Last updated on 2021-06-23 at 18:59:36

Welcome to MLRF official web page

This web page is the official web page for the MLRF course taught at EPITA. Students should find listed here (almost) all the resources they need for this course.

Teachers: Joseph Chazalon (lectures + practice), Olivier Ricou (practice), Julie Rivet (practice), Yizi Chen (practice).

Students’ weekly workflow should be:

  1. Friday, 09:30-10:00: Answer the weekly quiz on Moodle.
  2. Friday, 10:00-12:00: Attend the lecture using Teams.
  3. Friday, 14:00-17:00: Work on the practice session and join the discussion using Teams.
  4. Before next Friday: (for sessions 4, 5 and 6 only) Complete the assignment and submit your results using Moodle.

Tools we are using

We will try to use the right tool for the right job. Here are the tools and their job(s).

Setting up a programming environment on your computer

You need to set up a programming environment on your computer to complete this course. We tried to make this as easy as possible.

We use Jupyter, a notebook interface for scientific Python. We provide you with notebooks that you have to edit to complete each practice session.

To get a working environment, you first need to install a recent (3.7+) Python environment. Then, you need to install some packages to get all the necessary tools We recommend using pip, the Python package installer, as follows;

pip install --user \
    jupyter \
    matplotlib \
    numpy \
    opencv-contrib-python-headless \
    scikit-image \

You may need to edit your $PATH and add $HOME/.local/bin to the list of paths.

Then, you should be able to navigate to a directory containing Jupyter Notebooks (.ipynb files) and start a Jupyter server using

jupyter notebook

This should automatically launch a browser and let you interact with notebooks. We recommend that you read those two resources to get Jupyter’s basics:

Using EPITA lab computers

Course resources are available on the AFS at the following mount point: /afs/

To save your Jupyter and IPython configurations you may want to use the following commands:

mkdir -p ~/afs/.confs/jupyter/
mkdir -p ~/afs/.confs/ipython/
ln -sf ~/afs/.confs/jupyter/ ~/.jupyter
ln -sf ~/afs/.confs/jupyter/ ~/.ipython



May 14 – May 21

May 21 – May 28

May 28 – June 4

June 4 – June 11

June 18 – June 25

June 25 – July 2