Скачать или смотреть Exploring Hidden Markov Models | Julia Christina Costacurta

Exploring Hidden Markov Models | Julia Christina Costacurta

Hidden Markov Models (HMMs) are used to describe and analyze sequential data in a wide range of fields, including handwriting recognition, protein folding, and computational finance. In this workshop, we will cover the basics of how HMMs are defined, why we might want to use one, and how to implement an HMM in Python. This workshop might be of particular interest to attendees from May 25’s “Intro to Markov Chains and Bayesian Inference” session. Introductory background in probability, statistics, and linear algebra is assumed.

This workshop was conducted by Julia Christina Costacurta, PhD Candidate at Stanford University

Useful resources for this workshop:
https://bit.ly/hmm_presentation
https://bit.ly/hmm_tutorial_notebook

Learn more about WiDS Workshops: widsconference.org/workshops

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