UnivIS
Information system of Friedrich-Alexander-University Erlangen-Nuremberg © Config eG 

HS Deep Learning for NLP (HSprakt)

Lecturer
Prof. Dr. Stefan Evert

Details
Hauptseminar
2 cred.h, ECTS studies, ECTS credits: 5
Bachelor
Time and place: Wed 10:15 - 11:45, 01.019

Prerequisites / Organisational information
Participants must register for the StudOn course linked below. Seminar places are assigned on a first come, first served basis.

Contents
Deep neural networks – also known as deep learning – have attracted significant attention in recent years. They have had a transformative influence on natural language processing (NLP) and artificial intelligence (AI), with numerous success stories and even claims of superhuman learning performance in certain tasks. According to Young et al. (2017), more than 70% of the papers presented at recent NLP conferences made use of deep learning techniques.
This seminar will focus on the application of deep learning techniques to natural language processing tasks and on the topic "Social Bots: Danger or Myth?".

Recommended literature
  • Representation Learning: A Review and New Perspectives, Yoshua Bengio, Aaron Courville, Pascal Vincent, Arxiv, 2012.
  • Deep Learning, Yoshua Bengio, Ian Goodfellow, Aaron Courville, MIT Press

  • Goldberg, Yoav (2017). Neural Network Methods for Natural Language Processing. Number 37 in Synthesis Lectures on Human Language Technologies. Morgan & Claypool.

  • Young, Tom; Hazarika, Devamanyu; Poria, Soujanya; Cambria, Erik (2017). Recent trends in deep learning based natural language processing. CoRR, abs/1708.02709. http://arxiv.org/abs/1708.02709

  • http://deeplearning.stanford.edu/wiki/index.php/UFLDL_Tutorial

  • http://deeplearning.net/tutorial/

  • Stanford University CS 224: Deep Learning for NLP (http://cs224d.stanford.edu/)

  • University of Oxford: Deep Natural Language Processing (https://github.com/oxford-cs-deepnlp-2017/lectures)

ECTS information:
Credits: 5

Additional information
Expected participants: 5, Maximale Teilnehmerzahl: 20
www: https://www.studon.fau.de/crs2686653.html
Registration is required for this lecture.
Registration starts on Monday, 23.7.2018, 9:00 and lasts till Wednesday, 17.10.2018, 12:00 über: StudOn.

Department: Chair of Computational Corpus Linguistics (Prof. Dr. Evert)
UnivIS is a product of Config eG, Buckenhof