are now very commonly used in the Machine-Learning (ML) community.
Preliminary configuration
IF YOU WORK ON COMPUTERS IN ONE OF THE PRACTICAL SESSION ROOMS OF MINES ParisTech (L.117, L.119, L.120, L.022, etc), NOTHING NEEDS TO BE INSTALLED, BUT YOU NEED TO BOOT IN **LINUX**.
Just launch a Terminal window, and first ADAPT THE VALUE OF the "PATH" variable:
export PATH=/opt/anaconda3/bin:$PATH
Then, start jupyter-notebook in the terminal, by just typing:
jupyter-notebook
This shall open *in your web navigator* a kind of "explorer" allowing you to find, open, and then execute any notebook (files with .ipynb extension) present on your computer.
If you work somewhere else, or on your own laptop, then you must first make sure that Python, SciKit-Learn, and jupyter-notebook are properly installed.
The easiest way to install all you need on ANY computer (e.g. your own laptop) with ANY OS (Linux, Windows or MacOS) is to INSTALL Anaconda, which is a large "all in one" package (Jupyter, python, and common libraries) existing for ALL common Operating Systems (Windows, MacOS, and Linux). Once this software is installed on your computer, you shall only need to start jupyter-notebook, which will open in your web navigator a kind of "explorer" allowing you to find, open, and then execute any notebook (files with .ipynb extension)present on your computer.
Starting the practical session
First download somewhere on your computer the notebook of this practical session: dt-rf-boosting-notebook.ipynb
Then, start jupyter-notebook, search, find and open the notebook you have just downloaded.
Assignments of the practical session
They are described directly in the notebook, so you shall read them after opening it with Jupyter. However, you can also view them before in non-interactive HTML format if you wish.