392133 Vertiefung Neuronale Netze (V) (SoSe 2018)
Contents, comment
-
Mit der Vorlesung "Vertiefung Neuronale Netze" werden die im Modul "Neuronale Netze und Lernen" erworbenen Grundkenntnisse im Bereich neuronaler Netze und Lernalgorithmen weiter vertieft. Insbesondere werden weitere Netzmodelle wie Lokal Lineare Karten, Hyperbolische Selbstorganisierenden Karten, Growing Neural Gas, Radiale Basisfunktionen, sowie Eigenschaften und Lernverfahren für dynamische rekurrente Netze, insbesondere zur Zeitserienvorhersage behandelt.
Dabei werden häufig Beispiele aus der Mustererkennung herangezogen, um praktische Aspekte wie Vorverarbeitung, Merkmalselektion, Techniken zur Konvergenzbeschleunigung und Wahl einer geeigneten Netzarchitektur zu illustrieren.
Teilnahmevoraussetzungen, notwendige VorkenntnisseModul "Neuronale Netze und Lernen"
Requirements for participation, required level
-
Die Vorlesung wendet sich an einschlägig interessierte Studenten der Informatik, Mathematik und Linguistik im Hauptstudium. Neuronale Netze und Lernen
Bibliography
-
David MacKay: "Gaussian Processes Basics" (video lecture)
Iain Murray: "Markov Chain Monte Carlo" (video lecture)
External comments page
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period | |
|---|---|---|---|---|---|
| weekly | Di | 8-10 | X-E0-205 | 17.04.2018 | |
| weekly | Di | 8-10 | X-E0-205 | 24.04.-22.05.2018
not on: 5/1/18 / 5/22/18 |
|
| one-time | Di | 8-10 | T2-227 | 29.05.2018 | |
| weekly | Di | 8-10 | U2-113 | 29.05.-20.07.2018
not on: 5/29/18 / 6/19/18 / 6/26/18 |
|
| one-time | Di | 8-10 | V2-105/115 | 26.06.2018 |
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-M-Inf-VNN Vertiefung Neuronale Netze | Vertiefung Neuronale Netze | Ungraded examination
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.
- Registered number: 42
- This is the number of students having stored the course in their timetable. In brackets, you see the number of users registered via guest accounts.
- Address:
- SS2018_392133@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_121301295@ekvv.uni-bielefeld.de
- Coverage:
- 15 Students to be reached directly via email
- Notes:
- Additional notes on the electronic mailing lists
- Email archive
- Number of entries 0
- Open email archive
- Last update basic details/teaching staff:
- Thursday, January 11, 2018
- Last update times:
- Wednesday, April 18, 2018
- Last update rooms:
- Wednesday, April 18, 2018
- Type(s) / SWS (hours per week per semester)
- lecture (V) / 2
- 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=121301295
- Send page to mobile
-
Click to open QR code
Scan QR code:
- ID
- 121301295