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Principles of Data Science

You're reading from   Principles of Data Science Mathematical techniques and theory to succeed in data-driven industries

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Product type Paperback
Published in Dec 2016
Publisher Packt
ISBN-13 9781785887918
Length 388 pages
Edition 1st Edition
Languages
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Author (1):
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Sinan Ozdemir Sinan Ozdemir
Author Profile Icon Sinan Ozdemir
Sinan Ozdemir
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Toc

Table of Contents (15) Chapters Close

Preface 1. How to Sound Like a Data Scientist 2. Types of Data FREE CHAPTER 3. The Five Steps of Data Science 4. Basic Mathematics 5. Impossible or Improbable – A Gentle Introduction to Probability 6. Advanced Probability 7. Basic Statistics 8. Advanced Statistics 9. Communicating Data 10. How to Tell If Your Toaster Is Learning – Machine Learning Essentials 11. Predictions Don't Grow on Trees – or Do They? 12. Beyond the Essentials 13. Case Studies Index

Overview of the five steps

The five essential steps to perform data science are as follows:

  1. Asking an interesting question
  2. Obtaining the data
  3. Exploring the data
  4. Modeling the data
  5. Communicating and visualizing the results

First, let's look at the five steps with reference to the big picture.

Ask an interesting question

This is probably my favorite step. As an entrepreneur, I ask myself (and others) interesting questions every day. I would treat this step as you would treat a brainstorming session. Start writing down questions regardless of whether or not you think the data to answer these questions even exists. The reason for this is twofold. First off, you don't want to start biasing yourself even before searching for data. Secondly, obtaining data might involve searching in both public and private locations and, therefore, might not be very straightforward. You might ask a question and immediately tell yourself "Oh, but I bet there's no data out there that can help me,&quot...

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