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Data Science : 2 Books - Data Analytics For Beginners And Markov Models - Tech World

Data Science

2 Books - Data Analytics For Beginners And Markov Models

By: Tech World

Paperback | 28 February 2018

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Data Science: 2 Books - Data Analytics For Beginers and Markov Models

Data Analytics For Beginers

Are you ready to discover why data analytics is the only hope for fact based decisions?

Would you like learn how insightful-driven decisions can help organizations manage their strategic, operation and financial performance that can help them increase their shareholder value?

This book explores all the concepts about data analytics that can help any beginner to master data analytics and its applications in several industries.


Chapter one provides an overview of data analytics where the foundations of data analytics are explained in details. If you want to get started right away, you'll also learn the requirements for data scientists in this chapter.

In chapter two, a detailed discourse on conducting analytic data research is provided to give you a big picture view of how data analytics is done.

In chapter three, descriptive statistics is explored where you'll learn measures of central tendency and measures of dispersion.

Chapter four reviews all the charts and graphs that you can use to communicate your analytic results.

In chapter five, you'll learn the applications of data analysis in organizations. Finally, in chapter six, you'll learn some of the valuable tools that can help you advance your professional career in data analytics. You'll also learn why smart contracts are emerging as the next technologies for smart data analysis.


Take action today and discover the power of Data Analytics

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Markov Models

Do you want to MASTER data science?

Learn how machine learning systems can carry out multifaceted processes by learning from data?

Understand markov models and how they can help your correctly forecast future events?

Want to explore practical implementations of Markov models in Python programming environment?



The aim of machine learning is to train the computers or machine to learn on its own and make informed decisions in a relatively shorter time than what human beings can do.

The primary objective of this book is to provide you with all the ins and outs of Markov models and unsupervised machine learning over a range of multi-faceted applications. Specifically, the book will explore practical implementations of Markov models in Python programming environment.

You'll discover:

- Types of machine learning algorithms

- The mathematics behind markov algorithms

- Application of markov models in python programming

- Application of markov models in
- gaming
- Speech recognition
- Weather reporting

and much much more!

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