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Markov Models Supervised and Unsupervised Machine Learning: Mastering Data Science & Python

Markov Models Supervised and Unsupervised Machine Learning: Mastering Data Science & Python

          
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About the Book

Markov Models Supervised and Unsupervised Machine Learning: Mastering Data Science & Python
BONUS Buy a paperback copy of this book NOW and you will get the Kindle version Absolutely FREE via Kindle Matchbook

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 & algorithms
What you'll Learn

  • Mathematics Behind Markov Algorithms
  • 3 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 book offers high value and is the greatest investment in your knowledge base you can make that will benefit you in the long run

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    Audible Link: https: //www.audible.com/t2/title?asin=B0767LQ99X


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    Product Details
    • ISBN-13: 9781976050008
    • Publisher: Createspace Independent Publishing Platform
    • Publisher Imprint: Createspace Independent Publishing Platform
    • Height: 203 mm
    • No of Pages: 126
    • Spine Width: 7 mm
    • Weight: 136 gr
    • ISBN-10: 1976050006
    • Publisher Date: 03 Sep 2017
    • Binding: Paperback
    • Language: English
    • Returnable: N
    • Sub Title: Mastering Data Science & Python
    • Width: 127 mm


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