Sequence Labelling

Sequence labeling

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.

2 courses cover this concept

CSE 447 and 517 Natural Language Processing

University of Washington

Winter 2022

This course provides a comprehensive overview of Natural Language Processing (NLP), including core components like text classification, machine translation, and syntax analysis. It offers two project types: implementation problem-solving for CSE 447, and reproducing experiments from recent NLP papers for CSE 517.

No concepts data

+ 16 more concepts

CS 124: From Languages to Information

Stanford University

Winter 2023

This course is centered on extracting information from unstructured data in language and social networks using machine learning tools. It covers techniques like sentiment analysis, chatbot development, and social network analysis.

No concepts data

+ 14 more concepts