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  • Markov Models: Supervised and Unsupervised Machine Learning

  • Mastering Data Science & Python
  • By: William Sullivan
  • Narrated by: Lukas Arnold
  • Length: 1 hr and 49 mins
  • 4.6 out of 5 stars (10 ratings)

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Markov Models: Supervised and Unsupervised Machine Learning

By: William Sullivan
Narrated by: Lukas Arnold
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Summary

Do you want to master data science?

Understand Markov models and learn the real world application to accurately predict future events.

Extend your knowledge of machine learning, python programming, and algorithms.

What you'll learn:

  • Mathematics behind Markov algorithms
  • Three main problems of Markov models and how to overcome them
  • Uses and applications for machine learning
  • Python programming
  • Speech recognition
  • Weather reporting
  • The Markov rule and Markov's model
  • Fundamental axioms of statistics and probability
  • Solutions
  • Theories
  • Artificial intelligence
  • Bayesian inference
  • Important tools used with HMM
  • And much, much more!

    The objective of this book is to teach you the essentials at the most fundamental level. You will learn the ins and outs of machine learning, and its real world applications. Also, specifically you will discover practical implementations of Markov models in Python programming.

    This audiobook offers high value and is the greatest investment in your knowledge base you can make that will benefit you in the long run. Why not take this opportunity to take advantage now and get ahead of everyone else?

    Get equipped with the knowledge you need to advance yourself today.

  • ©2017 Healthy Pragmatic Solutions Inc. (P)2017 Healthy Pragmatic Solutions Inc.
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    What listeners say about Markov Models: Supervised and Unsupervised Machine Learning

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    • Overall
      5 out of 5 stars
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      5 out of 5 stars

    Amazing book

    Great book on machine learning, in this book you can find the ins and outs of machine learning, and its real-world applications. Good book for beginners!

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      5 out of 5 stars
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      5 out of 5 stars

    great book

    Very Informative. Great book a friend of mine lent me this book to read as I am new to machines and I needed to get some information and this book helped greatly. I would encourage anyone who want to learn about machines to get this book right away.

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    Thanks to the author.....

    I think this is a very good book. The author did a good job with this book. I would recommend for all.

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      5 out of 5 stars
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    easy to understand

    The simplest Markov model is the Markov chain. It models the state of a system with a random variable that changes through time.

    By listening this book, I was able to learn the foundation of Markov Models, Markov chains, hidden Markov models and many useful information. Great read. easy to understand.

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      5 out of 5 stars

    nice

    This is a very interesting book about Markov Models: Introduction to Markov Chains, Hidden Markov Models and Bayesian networks. In it I listened a lot of interesting and informative about Foundations of Markov Models, Case Study: Google PageRank and Inference Tasks

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      5 out of 5 stars

    what i expected

    Great introduction to marcov models, which is a term that gets confused a great deal.

    Clear and simple, in my case, it's all I needed, but it can get you started, if you want to go deeper

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    useful book

    This book is full of information that really helps you master data science. William Sullivan clearly knowledgeable of this thing. Educative book.

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    5 stars

    ARTIFICIAL INTELLIGENCE is the topic of the moment for IT professionals and now is the time to know this technology and start your preparation to surf this wave that is changing the way we use Information Technology

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    Love this book

    Many books I read for python programming but this is a different book basically author provide details about how can we do work with Markov Models in python programming.

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      1 out of 5 stars
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      3 out of 5 stars

    Unintelligible in audio form

    Don't bother trying to listen to this, it's a direct readout of physical copy without any consideration for the change in medium

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