This repository contains a set of excercises prepared for the 2017 version of the Machine Learning course offered at the Faculty of Mathematics, Physics and Informatics of Comenius University in Bratislava, Slovakia. It consists of a number of Jupyter notebooks and associated Python files.

The course goes provides an intoduction into the field of Machine Learning, while these excercises aim to give an opportunity to get practical experience with some of the most often used methods.

In order to use this repository, it needs to be downloaded first. If git is available, this can be done as easily as running:

    $ git clone https://github.com/NaiveNeuron/ml_exercises.git

Another option is downloading the .zip file from the following link:

    https://github.com/NaiveNeuron/ml_exercises/archive/master.zip

and extracting it to a ml_exercises repository.

It seems that by far the easiest way of getting all required dependences, especially the Jupyter notebooks is installing the Anaconda distribution.

Once the jupyter package has been installed in the previous sections, running the notebooks should be as easy as running the following in the ml_exercises directory:

    $ jupyter notebook

On Debian boxes, it is advisable to run the following command:

    $ jupyter-notebook

Should you run into any problem when trying to set up the environment for running these notebooks, please feel free to open an issue with a detailed description of your problem.