Vorlesungen/Details

MAT003

An introduction to machine learning

EXAM

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 gabriele.visentin@math.uzh.ch.
Final project deadline: 20.01.2020 at 23:59.

MAILING LIST

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 gabriele.visentin@math.uzh.ch asking to be added to the mailing list.

SOME INFORMATION ON EXERCISE CLASSES

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 (https://www.anaconda.com/distribution/).

Vorlesungen

Zeitraum:
10:15 - 12:00

Raum:
Y17M05 Plätze: 103

VVZ Link

Übungen

08:00 - 09:45

Y27H28
Plätze: 50

Exercises An introduction to machine learning Gr.2
Tutor: Marcel Fenzl

15:00 - 17:00

Y13M12
Plätze: 44

Exercises An introduction to machine learning Gr.3

10:15 - 12:00

Y27H28
Plätze: 50

Exercises An introduction to machine learning Gr.1
Tutor: Gabriele Visentin

Online Exercise submission

Exercise Streams

This lecture offers a video stream

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HOW TO USE THESE NOTEBOOKS?

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 https://jupyter.org/try 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.

Prüfung

Modul: 20.01.2020 , Raum: n.n. Plätze: ?, Typ: n.n.
Project - details follow from lecturer
Repetition: 31.08.2020 , Raum: No room needed Plätze: ?, Typ: schriftlich
Task to hand in, deadline 31.08.2020

Institut für Mathematik

Vorlesungen/Details

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