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Probability: 2 Manuscripts – Probability with Permutations and Markov Models

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Understanding probability as unique and stimulating theory which goes beyond conventional mathematics , will give you better perspective of the world around you. The first part of the book explains the fundamentals of probability in clear and easy to understand way even if you are not familiar with mathematics at all and you are just starting your journey towards this particular field of science . In the following sections of the book, the subject is explained in wider context along with importance of permutations and combinations in probability and their applications to a variety of scientific problems as well as the importance of probability in real life situations.

This book will offer you an insight into the Hidden Markov Models as well as the Bayesian Networks . Additionally, by reading this book, you will also learn algorithms such as Markov Chain Sampling . Furthermore, this book will also teach you how Markov Models are very relevant when a decision problem is associated with a risk that continues over time, when the timing of occurrences is vital as well as when events occur more than once. This book highlights several applications of Markov Models . Lastly, after purchasing this book, you will need to put in a lot of effort and time for you to reap the maximum benefits.

123 pages, Kindle Edition

Published July 2, 2017

6 people are currently reading

About the author

Steven Taylor

17 books
Librarian Note: There is more than one author by this name in the Goodreads database.

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Profile Image for Jeff Mottishaw.
7 reviews
December 8, 2017
Superficial and poorly written

If you want to learn probability theory or Markov models, this book is not for you. Not only was it poorly written, it only explained concepts in general terms without providing proofs or concrete examples. While it doesn’t claim to be a textbook, I was disappointed that no problems or other tools to check understanding were given. To be honest, Wikipedia would be a better resource for either probability theory or Markov modeling.
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