Markov Models: Supervised and Unsupervised Machine Learning Audiobook By William Sullivan cover art

Markov Models: Supervised and Unsupervised Machine Learning

Mastering Data Science & Python

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Markov Models: Supervised and Unsupervised Machine Learning

By: William Sullivan
Narrated by: Lukas Arnold
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About this listen

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.
    Engineering Mathematics Machine Learning Data Science Programming Artificial Intelligence
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    Informative Book • Clear Explanations • Comprehensive Treatment • Useful Introduction
    Highly rated for:
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    This is the good book to start Markov model.well organized. They have taken till the first order of Markov chain but whatever this book explains is precise and clear. It was a fairly quick read and I learned a lot.

    easy to understand

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    heard about this book from a friend. Glad that this book explained the basics first because I am not very familiar with python yet. It made learning Markov model fun and easy! Everything was explained clearly. and all you need to know about markov is in here! I highly recommend this book ......... 5 stars for this!

    glad to have this book

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    Great explanation. The author Steven Taylor shows us here what is Markov Models, how it works, how it helps in algorithm, Hidden Markov Models etc. This book helps me a lot to understand Markov Models

    extrodinary

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    Markov Models gives me new knowledge in various fields. The author should be commended for putting together the topic and pointing out the potential uses of the tool. Highly recommended this book

    good book

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    I like the book. But I gave 4 stars for this one I bought because it contains too many types. I have gotten some background in probability so I wished I could guess what their right words should be.

    4 stars

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    This book provides general information and how to use it in real life. To my mind, it will suit everyone who wants to know more and seeks self-development. This book is not easy, but very interesting and useful. I first listened about such models. This is quite interesting. I learned Markov Models from this book

    highly recommended

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    Thank to my best friend for sharing this book. I find this book very informative and also this book has impressive introduction about markov models. Great !

    thanks to author

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    This is an informative guide for the reader indeed. The Markov models give amazing flexibility in arranging of events. In this book you'll learn how to deal with impossible machine learning issues in a short period of time. I have the tools, code, and processes predicted that would acceptably use Markov Models for any event. I recommend this book.

    INFORMATIVE GUIDE

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    Sure, I had only basic knowledge of Markov Models, but it was great to see the Python code !!! I really really felt like this is a great start to HMM beyond what I could have found searching myself, because people always assume you understand some concepts before & rushing through small details. While this book does rush, it is a very well calculated rush, since the author gives just enough keywords for me to look into without feeling lost. Thank you again for the wonderful read & the wonderful code. It is delightful to see probability models in Python code

    wonderful

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    Appropriate and right to the main issues. The author should be commended for putting together the topic and and pointing out the potential uses of this tool.

    great job

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