Institute of Mathematics

Lecture courses/details

Fall 19

An introduction to machine learning

Speaker: Ashkan Nikeghbali


The final project have been handed out to the groups via email on 16.12.2019. If you are a student taking the exam and you (or your group leader) have not received this email, please contact us as soon as possible at the email address
Final project deadline: 20.01.2020 at 23:59.


We want to establish a mailing list that will be used for urgent information about the course. If you are not a UZH student officially registered (e.g. you are from ETH and/or you're a ZGSM PhD student) send an email to asking to be added to the mailing list.


The first two classes will cover basic Python programming and some related packages (numpy, matplotlib, scikit-learn). Classes are meant to be interactive, therefore you should bring your own laptop with Python 3 pre-installed.
We suggest for first-time users to install Python 3 using the anaconda distribution (


Tu 10.15 - 12.00
Room: Y17M05


We 08.00 - 09.45
Exercises An introduction to machine learning Gr.2
Tutor: Marcel Fenzl
Th 15.00 - 17.00
Exercises An introduction to machine learning Gr.3
Fr 10.15 - 12.00
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