Name: Markov Models: Introduction to Markov Chains, Hidden Markov Models and Bayesian Networks (en Inglés)
Price: 140.39 PEN
Availability: InStock
Author: Chapmann, Joshua
ISBN: 9781978304871

portada Markov Models: Introduction to Markov Chains, Hidden Markov Models and Bayesian Networks (en Inglés)

Formato

Libro Físico

Autor

Joshua Chapmann

Editorial

Createspace Independent Publishing Platform

Idioma

Inglés

N° páginas

106

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.6 cm

Peso

0.17 kg.

ISBN13

9781978304871

Categorías

Fundamentos matemáticos

Markov Models: Introduction to Markov Chains, Hidden Markov Models and Bayesian Networks (en Inglés)

Joshua Chapmann (Autor) · Createspace Independent Publishing Platform · Tapa Blanda

Libro Físico

S/ 140,39

S/ 280,77

Ahorras: S/ 140,39

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Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Markov Models: Introduction to Markov Chains, Hidden Markov Models and Bayesian Networks (en Inglés)"

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