Markov Models - Joshua Chapmann - Books - Createspace Independent Publishing Platf - 9781978304871 - October 29, 2017
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Markov Models

Joshua Chapmann

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Markov Models

What is a MEMORYLESS predictive model?

Markov models are a powerful predictive technique used to model stochastic systems using time-series data. They are centered around the fundamental property of "memorylessness", stating that the outcome of a problem depends only on the current state of the system - historical data must be ignored.



This model construction may sound overly simplistic. After all, if you have historical data why not use it to develop more complete and well-informed models? Surely, it would lead to more accurate predictions.



However, when modelling time-series data where previous results are of limited relevance, a memoryless model delivers vast performance advantages. By considering only the present state, algorithms become highly scalable, stable, fast and, above-all-else, extremely versatile. Speech recognition is a perfect example - nearly all of today's speech recognition algorthms are built using Markov Models.



In this book we will explore why a Memoryless predictive model can be so advantageous to the modern tech industry. We will take a look at fundamental mathematics and high-level concepts alike, extending our understanding of the subject beyond the simple Markov Model.

You will learn... Foundations of Markov Models Markov Chains Case Study: Google PageRank Hidden Markov Models Bayesian Networks Inference Tasks

Media Books     Paperback Book   (Book with soft cover and glued back)
Released October 29, 2017
ISBN13 9781978304871
Publishers Createspace Independent Publishing Platf
Pages 106
Dimensions 152 × 229 × 6 mm   ·   167 g
Language English  

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