392027 Grundlagen Neuronaler Netze (V) (WiSe 2015/2016)

Contents, comment

This lecture/module is part of the international track and delivered in English.

The lecture discusses basic notions of machine learning, starting from supervised learning
for regression and classification. It further introduces standard neural networks models, the perceptron and the multi-layer perceptron. Tunrning to unsupervised learning, several algorithms for vector quantization are introduced, Hebb-learning, and Self-Organizing Maps.

Note that the lecture is organized with the help of unimoodle. You can self-subscribe by
logging on via unimoodle.uni-bielefeld.de and the password NN+ML2015. All course material, lecture notes, and exercises will be published through moodle only.

Requirements for participation, required level

Algorithmen und Datenstrukturen, Vertiefung Mathematik. NOTE that machine learning is an applied math topic - make sure that you recall the necessary basic math.

Bibliography

Part of the lecture will lean on C. Bishop, Pattern Recognition and Machine Learning, Springer 2006, in particular Chap. 1, Chap. 3.1-3.3 (linear models für regression), Chap 4.1. /4.2. (für classification) , Chap 5. (feedforward neural networks). Furthermore, lecture notes (in English) are available.

Teaching staff

Dates ( Calendar view )

Frequency Weekday Time Format / Place Period  
weekly Fr 10-12 H11 19.10.2015-12.02.2016
not on: 12/25/15 / 1/1/16

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Subject assignments

Module Course Requirements  
39-Inf-NN_ver1 Grundlagen Neuronaler Netze Neuronale Netze und Lernen I 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.

Degree programme/academic programme Validity Variant Subdivision Status Semester LP  
Bioinformatik und Genomforschung / Bachelor (Enrollment until SoSe 2011) Grundlagen Neuronaler Netze Wahlpflicht 5. aktive Teilnahme  
Informatik / Bachelor (Enrollment until SoSe 2011) Nebenfach Grundlagen Neuronaler Netze; Neuronale Netze und Lernen Wahlpflicht 5. aktive Teilnahme  
Kognitive Informatik / Bachelor (Enrollment until SoSe 2011) Neuronale Netze und Lernen Pflicht 5. aktive Teilnahme  
Molekulare Biotechnologie / Bachelor (Enrollment until SoSe 2011) Grundlagen Neuronaler Netze Wahlpflicht 5. aktive Teilnahme  
Naturwissenschaftliche Informatik / Bachelor (Enrollment until SoSe 2011) Neuronale Netze und Lernen Wahlpflicht 5. aktive Teilnahme  
Naturwissenschaftliche Informatik / Diplom (Enrollment until SoSe 2004) Robotik; Physik; Biologie; NNet; ME   Teilleistung mündliche Prüfung möglich HS
Studieren ab 50    

The lecture achieves 2 CP, the corresponding exercises 2 CP, and an oral exam, which is necessary to complete the modul, adds 1 CP. The detailed schedule for the exercises is
published through moodle.

The current module will be continued in the SS 2016 with the 5 CP module "Grundlagen Maschinelles Lernen" (Introduction to machine learning). Both modules are formally independent, but the SS 2016 will partially rely on the material presented now.

No eLearning offering available
Registered number: 89
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Address:
WS2015_392027@ekvv.uni-bielefeld.de
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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_60097124@ekvv.uni-bielefeld.de
Coverage:
11 Students to be reached directly via email
Notes:
Additional notes on the electronic mailing lists
Last update basic details/teaching staff:
Friday, December 11, 2015 
Last update times:
Wednesday, July 1, 2015 
Last update rooms:
Wednesday, July 1, 2015 
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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60097124