Over the past few years, research towards natural language processing has shown strong evidence as to the effectiveness of models that involve both hierarchical structure as well as statistical learning from corpora.
In this track you will study the state-of-the-art statistical models for complex language processing tasks such as parsing, language modeling and machine translation. A characteristic of some of these models is that they involve defining probability measures over hierarchical structure, e.g., trees and graphs. The track covers supervised as well as unsupervised methods for learning these models directly from large training corpora and provides the necessary background for research in Computational Linguistics and Natural Language Processing.
Besides the core curriculum the following courses are offered in the Natural Language Processing and Learning track:
* Unsupervised Language Learning (track course) * Statistical Structure in Language Processing (track course) * Web Text Mining * Intelligent Multimedia Systems * Machine Learning: Principles and Methods * Speech Perception and Production * Advanced Database Systems * Qualitative Reasoning
Minimum bachelor degree
Recipient: University of Amsterdam
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