Institute of Mathematics

Lecture courses/details

Fall 19


We 08.00 - 09.45
Y27H28 Seats: 24
Exercises An introduction to machine learning Gr.2
Tutor: Marcel Fenzl
Th 15.00 - 17.00
Y13M12 Seats: 20
Exercises An introduction to machine learning Gr.3
Fr 10.15 - 12.00
Y27H28 Seats: 24
Exercises An introduction to machine learning Gr.1
Tutor: Gabriele Visentin



No special software is needed!
Download the notebook from the link above. Your browser may mistaken the file for text and open it in a new browser window. In order to avoid this and in order to actually download the file, you must right-click on the link and select "Save linked content as" or "Save link as" or a similar item (the actual name depends on your browser and language), then download it in a folder in your computer.
Go to the website and click on "Try JupyterLab". A demo notebook will open in your browser (give it some time to load). Upload the Notebook you just downloaded and open it.

For a more comfortable experience, please consider downloading Jupyter from their website and install the software on your computer.
Notice that if you installed Python through Anaconda, Jupyter is already installed on your machine.

In case you have problems with Jupyter (either online or installed), you can download the pdf copy of the notebook above, but you will lose the interactivity of the code.


Module: 20.01.2020 , Room: n.n., Type: n.n.
Project - details follow from lecturer
Repetition: 31.08.2020 , Room: No room needed, Type: written exam
Task to hand in, deadline 31.08.2020

Module: MAT003 An introduction to machine learning