Introduction to machine learning and NLP with Keras
Natural Language Processing
A sample NLP task with ML
. Sentiment analysis
. Features
. Logistic Regression
LABORATORY: Sentiment analysis with logistic regression
Deep Learning neural network models have been successfully applied to natural language processing, and are now changing radically how we interact with machines (translation, search engines, Siri, Alexa, GPT and Bing Chat to name a few). These models are able to infer a continuous representation for words and sentences, and generalize to new tasks with much less training data. 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 GPT4, T5, BERT, and their use with fine-tuning and prompting, as well as instruction learning and human feedback. 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 hosted by the Ixa NLP research group at the HiTZ research center of the University of the Basque Country (UPV/EHU).
