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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 FREE CHAPTER 2. Types of Data 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

The why/how/what strategy of presenting

When speaking on a less formal level, the why/how/what strategy is a quick and easy way to create a presentation worthy of praise. It is quite simple, as shown:

  1. Tell your audience why this question is important without really getting into what you are actually doing.
  2. Then, get into how you tackled this problem, using data mining, data cleaning, hypothesis testing, and so on.
  3. Finally, tell them what your outcomes mean for the audience.

This model is borrowed from famous advertisements. The kind where they would not even tell you what the product was until 3 seconds left. They want to catch your attention and then, finally, reveal what it was that was so exciting. Consider the following example:

"Hello everyone, I am here to tell you about why we seem to have a hard time focusing on our job when the Olympics are being aired. After mining survey results and merging this data with company-standard work performance data, I was able to find a correlation...

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