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Markov Models: Supervised and Unsupervised Machine Learning

Mastering Data Science & Python

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Markov Models: Supervised and Unsupervised Machine Learning

Auteur(s): William Sullivan
Narrateur(s): Lukas Arnold
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À propos de cet audio

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.
    Mathématique Apprentissage automatique Science des données Programmation Intelligence artificielle
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