392033 Statistical foundations of machine learning (V) (SoSe 2025)

Contents, comment

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The course will be delivered by Alejandro Hernandez-Wences, and, due to visa delays, the course will only start on May 6, and then spill over into the term holidays.

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The main building blocks of the course are the following:
- Brief review of probability
- Notions of convergence for random variables
- The big picture of classical statistical inference
- The big picture of Bayesian statistical inference
- Point Estimation
- Hypothesis Testing

Additionally, during the course, we will point to connections with
the machine learning paradigm.

Requirements for participation, required level

Students are expected to have attended previous courses on Probability and Calculus (univariate and multivariate).

External comments page

https://www.techfak.uni-bielefeld.de/ags/bm/teaching/Bielefeld_StatML_syllabus.pdf

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  
weekly Di 16-18 U5-133 07.04.-18.07.2025

Subject assignments

Module Course Requirements  
39-Inf-WP-SSC Scientific and Soft-Computing (Basis) Einführende 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.


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Registered number: 15 (1)
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Address:
SS2025_392033@ekvv.uni-bielefeld.de
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13 Students to be reached directly via email
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Last update basic details/teaching staff:
Tuesday, May 13, 2025 
Last update times:
Wednesday, February 5, 2025 
Last update rooms:
Wednesday, February 5, 2025 
Type(s) / SWS (hours per week per semester)
lecture (V) / 2
Language
This lecture is taught in english
Department
Faculty of Technology
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517389427