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) and Nicolas Boutry (practice).

Teachers will be available online during scheduled sessions (Monday morning and afternoon).
Students must connect to and attend all online sessions.
Students must watch the lectures before the Q/A sessions.

Students’ weekly workflow should be:

1. Before Monday: watch the lecture (see below for links) and prepare questions.
2. On Monday morning: attend the Q/A session using Teams.
3. On Monday afternoon: work on the practice session and join the discussion using Teams.
4. Before Sunday evening: (for sessions 4, 5 and 6 only) complete the assignment and submit your results using Moodle.
5. On the next Monday morning (before the Q/A session): Complete the test about previous lecture and practice 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).

• This web site: to share files with you
• Teams:
  • for Q/A sessions and practice sessions with teachers
  • for assistance and chat between students themselves
• Moodle:
  • for graded tests
  • to submit results for practice sessions 4, 5 and 6
  • for the final feedback about the course
• email: on rare occasions for important communication about the course

Setting up a programming environment on your computer

You need to setup 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 (3.5+) 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 \
    scikit-learn

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:

• Jupyter Documentation - Running the Notebook
• Jupyter Notebook Overview

Calendar overview

Resources

Remarks:

• This list will be updated along the course.
• Elements as listed in the order you should use or complete them.
• For practice sessions, please see the README file in the student resource archive for instructions.
• Due to copyright restrictions, links to datasets will be sent using private group chat.