392180 Maschinelles Lernen im Web (MA-app) (V) (WiSe 2024/2025)

Contents, comment

The increasing availability of electronic information on the web requires novel technologies
to deal with these data. In particular, the algorithms have to deal with big and structured data.
In the lecture, a few topics of relevance in this realm will be tackled, including
graph clustering,
nolinear dimensionality reduction,
link analysis,
streaming algorithms.
The algorithms will be tested in the exercises using Python

The lecture will be given in English

Requirements for participation, required level

foundations in computer science and math, programming skills

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  
weekly Di 12-14 Unpublished 07.10.2024-31.01.2025

Hide passed dates <<

Subject assignments

Module Course Requirements  
39-M-Inf-AI-app Applied Artificial Intelligence Applied Artificial Intelligence: Vorlesung Student information
- Graded examination Student information
39-M-Inf-AI-app-foc Applied Artificial Intelligence (focus) Applied Artificial Intelligence (focus): Seminar Student information
- Ungraded examination Student information
39-M-Inf-INT-app Applied Interaction Technology Applied Interaction Technology: Vorlesung Student information
- Graded examination Student information
39-M-Inf-INT-app-foc Applied Interaction Technology (focus) Applied Interaction Technology (focus): Vorlesung Student information
- Graded examination Student information

The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.

Exercises (2LP) and written exam (3LP)

The lecture can be extended to a 10CP module by means of a combination with a project seminar (see module handbook)

No eLearning offering available
Address:
WS2024_392180@ekvv.uni-bielefeld.de
This address can be used by teaching staff, their secretary's offices as well as the individuals in charge of course data maintenance to send emails to the course participants. IMPORTANT: All sent emails must be activated. Wait for the activation email and follow the instructions given there.
If the reference number is used for several courses in the course of the semester, use the following alternative address to reach the participants of exactly this: VST_530314305@ekvv.uni-bielefeld.de
Notes:
Additional notes on the electronic mailing lists
Last update basic details/teaching staff:
Monday, February 17, 2025 
Last update times:
Monday, February 17, 2025 
Last update rooms:
Monday, February 17, 2025 
Type(s) / SWS (hours per week per semester)
lecture (V) / 2
Language
This lecture is taught in english
Department
Faculty of Technology
Questions or corrections?
Questions or correction requests for this course?
Planning support
Clashing dates for this course
Links to this course
If you want to set links to this course page, please use one of the following links. Do not use the link shown in your browser!
The following link includes the course ID and is always unique:
https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=530314305
Send page to mobile
Click to open QR code
Scan QR code: Enlarge QR code
ID
530314305