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15 Math Concepts Every Data Scientist Should Know

You're reading from   15 Math Concepts Every Data Scientist Should Know Understand and learn how to apply the math behind data science algorithms

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781837634187
Length 510 pages
Edition 1st Edition
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Author (1):
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David Hoyle David Hoyle
Author Profile Icon David Hoyle
David Hoyle
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Essential Concepts FREE CHAPTER
2. Chapter 1: Recap of Mathematical Notation and Terminology 3. Chapter 2: Random Variables and Probability Distributions 4. Chapter 3: Matrices and Linear Algebra 5. Chapter 4: Loss Functions and Optimization 6. Chapter 5: Probabilistic Modeling 7. Part 2: Intermediate Concepts
8. Chapter 6: Time Series and Forecasting 9. Chapter 7: Hypothesis Testing 10. Chapter 8: Model Complexity 11. Chapter 9: Function Decomposition 12. Chapter 10: Network Analysis 13. Part 3: Selected Advanced Concepts
14. Chapter 11: Dynamical Systems 15. Chapter 12: Kernel Methods 16. Chapter 13: Information Theory 17. Chapter 14: Non-Parametric Bayesian Methods 18. Chapter 15: Random Matrices 19. Index 20. Other Books You May Enjoy

Time Series and Forecasting

Time series data is very common. This makes time series data analysis an important and highly relevant topic. It also means that time series analysis is an enormous topic and one that we can’t fully cover here – see point 1 in the Notes and further reading section at the end of the chapter. Consequently, our focus in this chapter will be on introducing and explaining the key math concepts that are at the heart of any time series data. These concepts are also what underpin the dominant classical approach to time series modeling – ARIMA modeling. Therefore, we will unapologetically focus overwhelmingly on introducing and explaining ARIMA models. This is not to say that there aren’t alternative time series modeling techniques out there. However, any well-founded time series modeling technique has to deal with the core concepts that ARIMA modeling focuses on. Therefore, ARIMA modeling serves as a concise and useful way of explaining...

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