Introduction to Language Technology Applications (1st edition)
20 hour, 5 afternoon summer course
July 12th to 16th
*See also our sister course: Deep Learning for NLP* ( http://www.ixa.eus/dl4nlp/ )
Language Technology is increasingly present in many of the applications we use in our everyday activities and the need of experts that can develop applications based on Language Technology is an ever growing demand both in the industry and academia. This course will introduce some of the most commonly used techniques to build applications based on Language Technology. Thus, the attendees will learn how to apply techniques such as document classification, sequence labeling, as well as vector-based word representations (embeddings) and pretrained language models for core applications such as Opinion Mining, Named Entity Recognition, Fake News Detection or Question Answering.
The course will have a practical focus (laboratories and practical tasks) learning to use readily available LT toolkits (Spacy, Flair, etc.) based on machine and deep learning in a multilingual and multi-domain setting. The aim is to allow attendees to acquire the required autonomy to solve practical problems by applying and developing Language Technology applications.
The course is part of the NLP master (http://ixa.si.ehu.es/master/) hosted by the Ixa NLP research group at the HiTZ research center ( http://hitz.ehu.eus/)of the University of the Basque Country (UPV/EHU).
*COVID update:* The classes will be broadcasted live online. The practical labs will be also held online, in two split groups with one lecturer in each. Given our online teaching experience these last year, we are confident that we will be able to offer a high-quality and engaging course, both at the theoretical and hands-on practical sessions.
Student profile --------------------
Targeted to graduate students and professionals from a range of disciplines (linguistics, journalism, computer science, sociology, etc.) that need an applied introduction to Language Technology. This involves identifying the required linguistic resources, appropriate tools/libraries and techniques with the aim of acquiring the required autonomy to solve practical problems by applying and developing applications based on Language Technology.
*NOTE:* previous attendance to the *Deep Learning for Natural Language Processing* course (http://www.ixa.eus/dl4nlp/) held the previous week will help students to better understand the underlying algorithms of Language Technology applications.
Introduction: NLP toolkits (Spacy, Flair, etc.), Multilingual Information Extraction Text Classification: Fake news, stance, hyperpartisanism, argumentation Sequence Labelling: Named Entity Recognition, POS tagging, lemmatization Opinion Mining: Fine-grained and Aspect-based Sentiment Analysis, Domains Question Answering: Recasting tasks as QA, Transformers, multilingual transfer learning
Rodrigo Agerri, Ramon y Cajal Research Fellow Joseba Fernandez de Landa, FPI researcher Iker Garcia, FPI researcher
Practical details ---------------------
5 theoretical sessions with interleaved labs, 20 hours Scheduled July 12th to 16th 2021, 15:00-19:00
Teaching language: English Capacity: 60 attendants (First-come first-served). Cost: 274 euros (270 for UPV/EHU members). -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/html Size: 3848 bytes Desc: not available URL: <https://mailman.uib.no/public/corpora/attachments/20210429/ea0dd9e8/attachment.txt>