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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

Product type Paperback

Published in Dec 2016

Publisher Packt

ISBN-13 9781785887918

Length 388 pages

Edition 1st Edition

Languages

Python

Concepts

Data Science

Author (1):

Sinan Ozdemir

View More author details

Table of Contents (15) Chapters

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

Chapter 3. The Five Steps of Data Science

We have spent extensive time looking at the preliminaries of data science, including outlining the types of data and how to approach datasets depending on their type. This chapter will focus mostly on the third step of exploration. We will use the Python packages pandas and matplotlib to explore different datasets.

The rest of the chapter is locked

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