Natural Language Understanding
Master in Artificial Intelligence Systems
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Description
Natural Language is the fundamental means for humans to develop at the individual and social level.
Natural Language Understanding (NLU) is one of the fundamental ability of artificial intelligence systems ( AISs ). NLU enables AISs to have a dialogue with humans or comprehend vast amounts and types of natural language sources ( speech, text, or multimedia). In the first part of the course, we will provide the students with basic knowledge about the natural language structure from the lexicon to the document-level formal models. Throughout the lectures and lab sessions, we will present and provide students with the knowledge and hands-on skills of the machine learning models ( symbolic and neural ) and their applications to natural language modeling and understanding.
(Links below require UNITN credentials)
Let Us Know
Use the student-lecturer space on didattica-online or
the feedback form (anonymous).
Lectures:
Course Description (Incl. Assignments and Grading)
Natural Language: from Spoken to Written Language
Language Modeling
Large Language Models: Evaluation
Large Language Models: Architectures
Distributional Semantics and Word Vectors
Part-Of-Speech
Named Entities
Constituency and Dependency Grammars
Sequence Labeling for NLU
Sequence Labeling for NLU with Neural Networks
Lexical Semantics
Parsing Affective States: Sentiment Analysis
Labs:
Lab descriptions and notebooks in the "labmaterial"
folder on didattica-online.
Here you find compact descriptions and notebook links.
