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Forecasting Time Series Data with Facebook Prophet

Forecasting Time Series Data with Facebook Prophet

By : Greg Rafferty
4.9 (17)
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Forecasting Time Series Data with Facebook Prophet

Forecasting Time Series Data with Facebook Prophet

4.9 (17)
By: Greg Rafferty

Overview of this book

Prophet enables Python and R developers to build scalable time series forecasts. This book will help you to implement Prophet’s cutting-edge forecasting techniques to model future data with higher accuracy and with very few lines of code. You will begin by exploring the evolution of time series forecasting, from the basic early models to the advanced models of the present day. The book will demonstrate how to install and set up Prophet on your machine and build your first model with only a few lines of code. You'll then cover advanced features such as visualizing your forecasts, adding holidays, seasonality, and trend changepoints, handling outliers, and more, along with understanding why and how to modify each of the default parameters. Later chapters will show you how to optimize more complicated models with hyperparameter tuning and by adding additional regressors to the model. Finally, you'll learn how to run diagnostics to evaluate the performance of your models and see some useful features when running Prophet in production environments. By the end of this Prophet book, you will be able to take a raw time series dataset and build advanced and accurate forecast models with concise, understandable, and repeatable code.
Table of Contents (18 chapters)
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1
Section 1: Getting Started
4
Section 2: Seasonality, Tuning, and Advanced Features
13
Section 3: Diagnostics and Evaluation

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.

In this chapter...

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Forecasting Time Series Data with Facebook Prophet
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