| dc.contributor.editor | Kruse, René-Marcel | |
| dc.contributor.editor | Säfken, Benjamin | |
| dc.contributor.editor | Silbersdorff, Alexander | |
| dc.contributor.editor | Weisser, Christoph | |
| dc.date.accessioned | 2021-08-06T09:34:57Z | |
| dc.date.available | 2021-08-06T09:34:57Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://doi.org/10.17875/gup2021-1608 | |
| dc.format.extent | VII, 166 | |
| dc.format.medium | Print | |
| dc.language.iso | eng | |
| dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/deed.de | |
| dc.subject.ddc | 330 | |
| dc.title | Learning Deep Textwork | |
| dc.title.alternative | Perspectives on Natural Language Processing and Artificial Intelligence | |
| dc.type | anthology | |
| dc.price.print | 30,00 | |
| dc.identifier.urn | urn:nbn:de:gbv:7-isbn-978-3-86395-501-4-5 | |
| dc.description.print | Softcover, 17x24 | |
| dc.subject.division | surveyed | |
| dc.relation.isbn-13 | 978-3-86395-501-4 | |
| dc.identifier.articlenumber | 8102152 | |
| dc.identifier.intern | isbn-978-3-86395-501-4 | |
| dc.subject.bisac | BUS000000 | |
| dc.subject.vlb | 780 | |
| dc.subject.bic | K | |
| dc.description.abstracteng | Artificial intelligence is considered to be one of the most decisive topics in the 21st century. Deep learning algorithms, which are the basis of many artificial intelligence applications, are of central interest for researchers but also for students that strive to build up academic knowledge and practical competencies in this field.
The Deep Learning Seminar at the University of Göttingen follows the central notion of the Humboldtian model of higher education and offers graduate students of applied statistics the opportunity to conduct their own research. The quality of the results motivated us to publish the most promising seminar papers in this volume. For the selected papers a review process was conducted by the lecturers.
The presented contributions focus on applications of deep learning algorithms for text data. Natural language processing methods are for example applied to analyse data from Twitter, Telegram and Newspapers. The research applications allow the reader to gain deep insights into some of the latest developments in the field of artificial intelligence and natural language processing from the perspective of students of whom many will take part in shaping the future research in this field. | |
| dc.notes.vlb-print | lieferbar | |
| dc.intern.doi | 10.17875/gup2021-1608 | |
| dc.identifier.purl | http://resolver.sub.uni-goettingen.de/purl?univerlag-isbn-978-3-86395-501-4 | |
| dc.format.chapters | - | |
| dc.intern.asin | 3863955013 | |
| dc.subject.thema | K | |
