*Deep Learning for Natural Language Processing (8th edition)*
20 hour, 5 afternoon summer course
July 5th to 9th
See also _Introduction to LT Applications_
<https://ixa.eus/iltapp>sister course one week later
Deep Learning neural network models have been successfully applied to natural language processing, and are now changing radically how we interact with machines (Siri, Amazon Alexa, Google Home, Skype translator, Google Translate, or the Google search engine). These models are able to infer a continuous representation for words and sentences, instead of using hand-engineered features as in other machine learning approaches. The seminar will introduce the main *deep learning models used in natural language processing*, allowing the attendees to gain *hands-on understanding and implementation* of them in Keras.
This course is a 20 hour introduction to the main deep learning models used in text processing, covering the latest developments, including *Transformers and pre-trained (multilingual) language models* like GPT, BERT and XLM-R. It combines *theoretical and practical hands-on classes*. Attendants will be able to understand and implement the models in Keras.
The course is part of the NLP master <https://ixa.eus/master/index.php?lang=en> hosted by the Ixa NLP research group <https://ixa.eus/?language=en> at the HiTZ research center <http://hitz.ehu.eus> of the University of the Basque Country (UPV/EHU) <http://www.ehu.eus>.
/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 -------------------- Addressed to professionals, researchers and students who want to understand and apply deep learning techniques to text. The practical part requires basic programming experience, a university-level course in computer science and experience in Python. Basic math skills (algebra or pre-calculus) are also needed.
- Introduction to machine learning and NLP with Keras
- Multilayer Perceptron and Word Embeddings
- Recurrent Neural Networks, Seq2seq, Neural Machine Translation
- Attention, Better Machine Translation and Natural Language Inference
- Pre-trained Transformers. BERTology
- Eneko Agirre, Full professor, member of IXA
- Oier Lopez de la Calle, Assistant professor, member of IXA
- Ander Barrena, Postdoc researcher at IXA
Practical details --------------------- 5 theoretical sessions with interleaved labs, 20 hours Scheduled July 5th to 9th 2021, 15:00-19:00
Teaching language: English Capacity: 60 attendants (First-come first-served). Cost: 274 euros (270 for UPV/EHU members).
Registration ---------------- Registration open: now to the 27th of June 2020 (or until room is full). Please register by email to amaia.lorenzo at ehu.eus <mailto:amaia.lorenzo at ehu.eus?subject=Registration to DL4NLP&cc=e.agirre at ehu.eus> (subject "Registration to DL4NLP" and CC e.agirre at ehu.eus). Same for any enquiry you might have. The university provides official certificates <https://www.ehu.eus/en/web/complementarios/ziurtagiri-eskaria>. Please apply AFTER completing the course. Public universities are not allowed to produce invoices, but we can provide a payment certificate.
Prerequisite ---------------- Basic programming experience, a university-level course in computer science and experience in Python. Basic math skills (algebra or pre-calculus) are also needed. Computer with Internet needed (no need to install anything).
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