The objective of this course is to introduce the field of Natural Language Processing (NLP) through the most used applications both in the academi a and the industry. The course contents will include basic techniques of NLP: document classification, sequence labeling for opinion mining, vector-based word representations (embeddings), and normalization and pre-processing of texts. Furthermore, the role of machine translation for professionals focusing mostly on the post-edition process. The course will have a practical focus based on laboratories and practical tasks learning to use NLP tools based on machine and deep learning.
Syllabus
Introduction to NLP: Practical Applications (Opinion Mining and Machine Translation).
Multilingual Document Classification: Sentiment Analysis and Fake News detection for news and social networks.
Sequence Labeling for Aspect Based Sentiment Analysis (ABSA).
Post-edtion and evaluation in Machine Translation.
