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Forecasting Time Series Data with Facebook Prophet

You're reading from Forecasting Time Series Data with Facebook Prophet

Product type Book

Published in Mar 2021

Publisher Packt

ISBN-13 9781800568532

Pages 270 pages

Edition 1st Edition

Languages

Concepts

Predictive Analytics

Author (1):

Greg Rafferty

Table of Contents (18) Chapters

Preface

1. Section 1: Getting Started

2. Chapter 1: The History and Development of Time Series Forecasting

3. Chapter 2: Getting Started with Facebook Prophet

4. Section 2: Seasonality, Tuning, and Advanced Features

5. Chapter 3: Non-Daily Data

6. Chapter 4: Seasonality

7. Chapter 5: Holidays

8. Chapter 6: Growth Modes

9. Chapter 7: Trend Changepoints

10. Chapter 8: Additional Regressors

11. Chapter 9: Outliers and Special Events

12. Chapter 10: Uncertainty Intervals

13. Section 3: Diagnostics and Evaluation

14. Chapter 11: Cross-Validation

15. Chapter 12: Performance Metrics

16. Chapter 13: Productionalizing Prophet

17. Other Books You May Enjoy

Chapter 2: Getting Started with Facebook Prophet

Prophet is an open source piece of software, which means that the entirety of the underlying code is freely available to anyone to inspect and modify. This gives Prophet a great deal of power as any user can add features or fix bugs, but it also has its downsides. Many closed source software packages, such as Microsoft Word or Tableau, come packaged in their own independent installation file with a neat graphical user interface to not only walk users through installation but also enable them to interact with the software once it's installed.

Prophet, in contrast, is accessed through either the Python or R programming languages and depends upon many additional open source libraries. This gives it great flexibility as users can tweak features or even add entirely new ones to suit their specific problem, but it comes with the downside of potentially difficult usability. That's what this book aims to simplify.

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Authors (1)

Greg Rafferty

Greg Rafferty is a data scientist in San Francisco, California. With over a decade of experience, he has worked with many of the top firms in tech, including Google, Facebook, and IBM. Greg has been an instructor in business analytics on Coursera and has led face-to-face workshops with industry professionals in data science and analytics. With both an MBA and a degree in engineering, he is able to work across the spectrum of data science and communicate with both technical experts and non-technical consumers of data alike.

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