This course presents topics in natural language processing with an emphasis on modern techniques, primarily focusing on statistical and deep learning approaches. The course provides an overview of the primary areas of research in language processing as well as a detailed exploration of the models and techniques used both in research and in commercial natural language systems.
Lernziel
The objective of the course is to learn the basic concepts in the statistical processing of natural languages. The course will be project-oriented so that the students can also gain hands-on experience with state-of-the-art tools and techniques.
Inhalt
This course presents an introduction to general topics and techniques used in natural language processing today, primarily focusing on statistical approaches. The course provides an overview of the primary areas of research in language processing as well as a detailed exploration of the models and techniques used both in research and in commercial natural language systems.
Literatur
Jacob Eisenstein: Introduction to Natural Language Processing (Adaptive Computation and Machine Learning series)
Leistungskontrolle
Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Es werden nur die öffentlichen Lernmaterialien aufgeführt.
Gruppen
Keine Informationen zu Gruppen vorhanden.
Einschränkungen
Plätze
Maximal 200
Vorrang
Die Belegung der Lerneinheit ist bis 24.09.2020 nur durch die primäre Zielgruppe möglich
Primäre Zielgruppe
Data Science MSc (261000)
Informatik MSc (263000)
Doktorat Informatik (264002)
DAS ETH in Data Science (266000)
CAS ETH in Informatik (269000)
Rechnergestützte Wissenschaften MSc (438000)
Leistungskontrolle als Semesterkurs