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Course: Deep Learning for Natural Language Processing (4,5 ECTS, February)

Are the meanings of these two words related? (Eneko’s Google Award 2015)

Course: Deep Learning for Natural Language Processing

    Course open to anyone, see details and pre-requisite information below.
    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.

Contents

Introduction to machine learning and NLP with Tensorflow, Deep learning, Word embeddings, Language modeling and recurrent neural networks, Convolutional neural networks, Attention mechanisms

Instructors :Eneko Agirre & Oier Lopez de Lacalle

Practical details

Part of the Language Analysis and Processing master program
Schedule: Twelve days, February 5-8, 19-22, 26-28 and March 1 (2018)
Time: 17:30 – 20:00
Where: Lab 0.1, Computer science faculty, San Sebastian
Teaching language: English
Capacity: 20 students (selected according to CV)
Price: 180€
4.5 ECTS credits

Registration

Pre-registration and contact: send an e-mail with CV to amaia.lorenzo@ehu.eus and e.agirre@ehu.eus
Pre-registration open: now to 24th of December
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.

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