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Lecture 7: Hidden Markov Models (HMMs)

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Marina Santini
Marina Santini

This document is a lecture on hidden Markov models (HMMs) given by Marina Santini at Uppsala University. The lecture covers the basics of HMMs, including Markov assumptions, observation sequences, problems with HMMs, the Viterbi, forward, and backward algorithms, modeling for part-of-speech tagging, learning, smoothing, and inference in HMMs, as well as applications of HMMs. The lecture acknowledges Joakim Nivre for course design and materials.

Educación
1 de 20
Machine Learning for Language Technology Lecture 7: Hidden Markov Models (HMMs) Marina Santini Department of Linguistics and Philology Uppsala University, Uppsala, Sweden Autumn 2014 Acknowledgement: Thanks to Prof. Joakim Nivre for course design and materials
Hidden Markov Models (1)
Hidden Markov Models (2)
A Simple HMM
Markov Assumptions
Observation Sequences
Problems for HMMs (1)
Problems for HMMs (2)
Viterbi
Forward Algo & Backward Algo
Forward-Backward Algo
Part-Of-Speech Tagging
Modeling (1)
Modeling (2)
Learning
Smoothing
Inference
HMM Applications
The end

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Lecture 7: Hidden Markov Models (HMMs)