Sequence labeling is a pattern recognition task in machine learning where categorical labels are assigned to each element of a sequence. It is often used for part-of-speech tagging, where the optimal label for a word depends on nearby words. Most sequence labeling algorithms use statistical inference and make a Markov assumption, with hidden Markov models being a common choice.
Carnegie Mellon University
Spring 2021
Focused on computational systems for human languages, this course introduces various NLP applications, such as translation and summarization. It encompasses a broad scope, from machine learning to linguistics, with a software engineering perspective.
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