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Principles of Data Science

You're reading from   Principles of Data Science A beginner's guide to essential math and coding skills for data fluency and machine learning

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781837636303
Length 326 pages
Edition 3rd Edition
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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 (18) Chapters Close

Preface 1. Chapter 1: Data Science Terminology 2. Chapter 2: Types of Data FREE CHAPTER 3. Chapter 3: The Five Steps of Data Science 4. Chapter 4: Basic Mathematics 5. Chapter 5: Impossible or Improbable – A Gentle Introduction to Probability 6. Chapter 6: Advanced Probability 7. Chapter 7: What Are the Chances? An Introduction to Statistics 8. Chapter 8: Advanced Statistics 9. Chapter 9: Communicating Data 10. Chapter 10: How to Tell if Your Toaster is Learning – Machine Learning Essentials 11. Chapter 11: Predictions Don’t Grow on Trees, or Do They? 12. Chapter 12: Introduction to Transfer Learning and Pre-Trained Models 13. Chapter 13: Mitigating Algorithmic Bias and Tackling Model and Data Drift 14. Chapter 14: AI Governance 15. Chapter 15: Navigating Real-World Data Science Case Studies in Action 16. Index 17. Other Books You May Enjoy

The Five Steps of Data Science

This chapter will dive into the five core steps involved in the data science process, with examples every step of the way. These five steps include defining a real problem, collecting and preprocessing the data, exploring and analyzing the data, drawing conclusions, and communicating results effectively.

We will also delve into the important topics of data exploration and data visualization. Data exploration involves examining the characteristics and patterns in your data to better understand it, while data visualization involves using graphs, charts, and other visual aids to represent and communicate your data and findings.

By the end of this chapter, you will have a solid understanding of the data science process and how to apply it to solve real-world problems. So, let’s get started!

We will also cover the following topics in this chapter:

  • An introduction to what data science really is
  • Exploring data effectively
  • Exploration...
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