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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

Basic symbols and terminology

In the following section, we will review the mathematical concepts of vectors, matrices, arithmetic symbols, and linear algebra, as well as some more subtle notations used by data scientists.

Vectors and matrices

A vector is defined as an object with both magnitude and direction. This definition, however, is a bit complicated. For our purpose, a vector is simply a one-dimensional array representing a series of numbers. Put another way, a vector is a list of numbers.

It is generally represented using an arrow or bold font, as shown here:

<math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><mrow><mrow><mover><mi>x</mi><mo stretchy="true">→</mo></mover><mi>o</mi><mi>r</mi><mi mathvariant="script">x</mi></mrow></mrow></math>

Vectors are broken into components, which are individual members of the vector. We use index notations to denote the element that we are referring to, as illustrated here:

<math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><mrow><mrow><mi>I</mi><mi>f</mi><mover><mi>x</mi><mo stretchy="true">→</mo></mover><mo>=</mo><mfenced open="(" close=")"><mtable columnwidth="auto" columnalign="center" rowspacing="1.0000ex 1.0000ex" rowalign="baseline baseline baseline"><mtr><mtd><mn>3</mn></mtd></mtr><mtr><mtd><mn>6</mn></mtd></mtr><mtr><mtd><mn>8</mn></mtd></mtr></mtable></mfenced><mi>t</mi><mi>h</mi><mi>e</mi><mi>n</mi><msub><mi mathvariant="script">x</mi><mn>1</mn></msub><mo>=</mo><mn>3</mn></mrow></mrow></math>

Note

In math, we generally refer to the first element as index 1, as opposed to computer science, where we generally refer to the first element as index 0. It is important to remember which index system you are using.

In Python...

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