Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Hidden Markov Models: Parameter Estimation, Inference, and Viterbi Algorithm

UofU Data Science via YouTube

Start learning Write review
Coursera Ad

AI, Data Science & Cloud Certificates from Google, IBM & Meta

Learn More → Corporate Finance Institute Ad

Learn Excel and Financial Modeling the Way Finance Teams Actually Use Them

Learn More →

Overview

Google, IBM & Meta Certificates – 40% Off
One Coursera Plus subscription covers most Professional Certificates on Coursera.
Unlock All Certificates
Learn about Hidden Markov Models (HMM) in this 34-minute lecture focusing on parameter estimation, inference, and the Viterbi algorithm. Explore the mathematical foundations and practical applications of HMMs, understanding how to estimate model parameters and perform efficient sequence analysis using dynamic programming techniques. Dive into the Viterbi algorithm's mechanics for finding the most likely sequence of hidden states in an HMM, with detailed explanations supported by comprehensive slides and examples.

Syllabus

HMM: Parameter estimation & inference; Viterbi

Taught by

UofU Data Science

Reviews

Start your review of Hidden Markov Models: Parameter Estimation, Inference, and Viterbi Algorithm

Start learning

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.