Exercise_ML

There are two different ways to approch the machine learning (ML) exercises of this course:

1) If you want to work directly on-line you have to work on the "notebooks" following these instructions:

Go on google colab and log with your google account (https://colab.research.google.com/)
Open the Github option and set the connection following what is written in the following picture :

Below there are instructions for the standard install of Python > 3.7 for the course.

Download the appropriate version of miniconda for your computing environment: https://conda.io/miniconda.html
Follow the "quick install" instructions to install miniconda on your machine: https://conda.io/docs/install/quick.html
Once you have installed miniconda, we need to set up a conda environment for our work. (To learn more about conda virtual environments, consult their docs: https://conda.io/docs/using/envs.html) From the command line (note this is slightly different on a Windows machine), enter the following: conda env create -f environment.yml
To activate the environment, this should be done prior to any work at the course, enter the following on the command line: conda activate OAR_ML_env
To exit the environment, type the following: conda deactivate

If you don't want to install Anaconda or python on your pc, you still can work on the notebooks:

go on google colab and log with your google account
open the Github option and set the connection with this repository (see the picture) :

If you are very new with python, please read these tutorials before the course:

All the notebooks we will use are coming from:

For any questions or problems don't hesistate to contact me at [email protected]