Natural Language Understanding
Master in Artificial Intelligence Systems
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Description
Natural Language is the fundamental means by which humans develop at the individual and social levels. Natural Language Understanding (NLU) is one of the fundamental capabilities of artificial intelligence systems (AISs). NLU enables AISs to comprehend vast amounts and types of natural language sources (speech, text, or multimedia) and to engage in dialogue with humans. In the first part of the course, we will provide students with core knowledge of natural language structure and empirical properties, from the lexicon to document-level formal models. Throughout the lectures and lab sessions, we will provide students with hands-on skills in 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
NLU with Neural Networks
Lexical Semantics
Parsing Affective States: Sentiment Analysis
Labs:
Lab descriptions, notebooks, and recordings (if available)
in the "labmaterial" folder on didattica-online.
Here you find compact descriptions and notebook links.
