Subject
Deep Learning
General details of the subject
- Mode
- Face-to-face degree course
- Language
- English
Description and contextualization of the subject
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 Tensorflow.Teaching staff
Name | Institution | Category | Doctor | Teaching profile | Area | |
---|---|---|---|---|---|---|
AGIRRE BENGOA, ENEKO | University of the Basque Country | Profesorado Pleno | Doctor | Bilingual | Computer Languages and Systems | e.agirre@ehu.eus |
AZCUNE GALPARSORO, GORKA | University of the Basque Country | Profesorado Agregado | Doctor | Bilingual | Science of Computation and Artificial Intelligence | gorka.azcune@ehu.eus |
BARRENA MADINABEITIA, ANDER | University of the Basque Country | Profesorado Adjunto (Ayudante Doctor/A) | Doctor | Bilingual | Computer Languages and Systems | ander.barrena@ehu.eus |
LOPEZ DE LACALLE LECUONA, OIER | University of the Basque Country | Profesorado Adjunto (Ayudante Doctor/A) | Doctor | Bilingual | Computer Languages and Systems | oier.lopezdelacalle@ehu.eus |
Competencies
Name | Weight |
---|---|
Learn skills to deal with strategies and tools for natural language processing. | 20.0 % |
Learn skills to deal with machine learning methods for natural language processing. | 20.0 % |
Ability to manage, adapt and improve the most relevant empirical methods for research in language technologies. | 20.0 % |
Ability to handle multimodal representations. | 20.0 % |
Ability to improve language understanding with visual information. | 20.0 % |
Study types
Type | Face-to-face hours | Non face-to-face hours | Total hours |
---|---|---|---|
Lecture-based | 20 | 30 | 50 |
Applied computer-based groups | 40 | 60 | 100 |
Training activities
Name | Hours | Percentage of classroom teaching |
---|---|---|
Computer work practice, laboratory, site visits, field trips, external visits | 100.0 | 40 % |
Lectures | 50.0 | 40 % |
Assessment systems
Name | Minimum weighting | Maximum weighting |
---|---|---|
Essay, Individual work and/or group work | 50.0 % | 50.0 % |
Works and projects | 50.0 % | 50.0 % |
Learning outcomes of the subject
Show understanding of deep learning systems, as well as the main architectures used in NLPDevelopment of basic deep learning systems applied to NLP problems.
Show knowledge about the latest advances in deep learning for NLP
Ordinary call: orientations and renunciation
Sistema de Evaluación ContinuaHerramientas y porcentajes de calificación:
Prueba escrita a desarrollar (%):
Realización de prácticas (ejercicios, casos o problemas) (%): 50
Trabajos individuales (%): 50
Sistema de Evaluación Final
Herramientas y porcentajes de calificación:
Prueba escrita a desarrollar (%): 50
Trabajos individuales (%): 50
Extraordinary call: orientations and renunciation
Sistema de Evaluación FinalHerramientas y porcentajes de calificación:
Prueba escrita a desarrollar (%): 50
Trabajos individuales (%): 50
Temary
1. Introduction to machine learning and NLP with Tensorflow2. Multilayer Perceptron
3. Word embeddings and recurrent neural networks
4. Seq2seq, neural machine translation and better RNNs
5. Attention, Transformers and Natural Language Inference
6. Pre-trained transformers, BERTology
7. Bridging the gap between natural languages and the visual world
Bibliography
Basic bibliography
Yoav Goldberg's Primer. http://u.cs.biu.ac.il/~yogo/nnlp.pdfKyunghyun Cho¿'s course notes. http://arxiv.org/pdf/1511.07916.pdf
The online version of the Goodfellow, Bengio, and Courville Deep Learning textbook. http://www.deeplearningbook.org/