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Markov Models: Definitive Guide to Understanding Unsupervised Machine Learning in Python: Definitive Guide to Understanding Unsupervised Machine Learning in Python

Markov Models: Definitive Guide to Understanding Unsupervised Machine Learning in Python: Definitive Guide to Understanding Unsupervised Machine Learning in Python

          
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About the Book

Have You Ever Wondered How Artificial Intelligence And Data Science Work? Are you looking to learn about machine learning and how it relates to these topics

Do Hidden Markov Models sound familiar and you want to learn more about them?

If so, "Markov's Model And Unsupervised Machine Learning In Python" is THE book for you!

It covers all you need to know about Markov's Model and machine learning and how to implement them in Python!

Machine learning has become extremely popular over the last decade or two. Everyone from businesses looking for customer profiling and fraud detection, to WEB miners looking to for text mining and document search capabilities, to those working in medicine and astronomy and even on the Human Genome Project have been using machine learning to perform their work.

The consulting company, McKinsey, put out a report in 2016 that machine learning's greatest potential across all industries polled lies in its abilities of forecasting and predictive analytics. This means that machine learning could change the face of industries from media to agriculture to automotive and so many in between! If you are a programmer, you don't want to be behind the times - you must learn machine learning programming tools and methods before it's too late, and this is the perfect place to start.

What Separates This Book From The Rest?

Most other books assume you have a working knowledge of various topics or, alternatively, remain too basic to be useful. This book teaches you from the basics to the intermediate level so that you can grow in understanding as you read. Instead of starting out by assuming you know statistical and probability axioms, we begin by introducing those and move through to explain Markov's Model, Hidden Markov Model problems, and much more! Let's take a brief look at what you will learn by reading this book.

You Will Learn The Following:

  1. Fundamental Axioms Of Statistics And Probability
  2. The Markov Rule And Markov's Model
  3. The Hidden Markov Model (HMM)
  4. The Three Problems Of HMMs
  5. Solutions To The Three HMM Problems
  6. What Is Machine Learning?
  7. Uses And Applications For Machine Learning
  8. Application Of HMMs In Python And The Solutions
  9. And much more!

So don't delay it any longer. Take this opportunity and invest in this guide now.

You will be amazed by how much your understanding of these topics can improve in just this short read! Your journey to understanding machine learning is just beginning! A whole new world of possibilities awaits you!

Download This Guide Now!

See you inside!


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Product Details
  • ISBN-13: 9781974600243
  • Publisher: Createspace Independent Publishing Platform
  • Publisher Imprint: Createspace Independent Publishing Platform
  • Height: 229 mm
  • No of Pages: 58
  • Weight: 95 gr
  • ISBN-10: 1974600246
  • Publisher Date: 15 Aug 2017
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Width: 152 mm


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