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||'''Dozent:''' || Wojciech Samek (wojciech.samek@hhi.fraunhofer.de) || | ||'''Dozent:''' || Dr. Wojciech Samek (wojciech.samek@hhi.fraunhofer.de) || |
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This seminar takes a closer look at a very hot topic in machine learning: Deep Learning. Students will read, understand, evaluate and present selected research papers on deep learning. At the end of the semester, each student will present his/her topic in a 25 min talk (+ 5 min questions) in English. The topics of the seminar are: * '''Deep Learning Overview''' * '''Deep Learning vs. Shallow Learning''' * '''How to train a DNNs (trips & tricks)''' * '''Understanding / Interpreting DNNs''' * '''DL in image classification’'' * '''DL for object detection''' * '''DL in speech recognition''' * '''DL in text analysis’'' * '''DL in video analysis''' * '''DL in fMRI analysis''' * '''Deep Boltzmann Machines’'' * '''Recurrent Nets''' |
Block-Seminar "Hot Topics in Machine Learning: Deep Learning"
Termine und Informationen
Erster Termin für Themenvergabe |
Freitag, 17.04.2015, 10am-12pm in MAR 4.033 |
Verantwortlich |
Prof. Dr. Klaus-Robert Müller |
Dozent: |
Dr. Wojciech Samek (wojciech.samek@hhi.fraunhofer.de) |
Sprache |
Englisch |
Anrechenbarkeit |
Wahlpflicht LV im Modul Maschinelles Lernen II (Informatik M.Sc.) |
This seminar takes a closer look at a very hot topic in machine learning: Deep Learning.
Students will read, understand, evaluate and present selected research papers on deep learning. At the end of the semester, each student will present his/her topic in a 25 min talk (+ 5 min questions) in English.
The topics of the seminar are: * Deep Learning Overview
Deep Learning vs. Shallow Learning
How to train a DNNs (trips & tricks)
Understanding / Interpreting DNNs
DL in image classification’
DL for object detection
DL in speech recognition
DL in text analysis’
DL in video analysis
DL in fMRI analysis
Deep Boltzmann Machines’
Recurrent Nets