Book Image

Forecasting Time Series Data with Facebook Prophet

By : Greg Rafferty
Book Image

Forecasting Time Series Data with Facebook Prophet

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)
1
Section 1: Getting Started
4
Section 2: Seasonality, Tuning, and Advanced Features
13
Section 3: Diagnostics and Evaluation

Chapter 5: Holidays

Because Prophet was designed to handle business forecasting cases, it is important to include the effects of holidays, which naturally play a large role in business activities. Just as bike-share commuters will ride more frequently in the summer than the winter, or on Tuesdays than on Sundays, it is reasonable to hypothesize that they would ride less than otherwise expected on Thanksgiving, for example.

Fortunately, Prophet includes robust support for including the effects of holidays in your forecasts. Furthermore, the techniques Prophet has for including the effects of holidays can be used to add any holiday-like event, such as the food festival that we will model in this chapter.

Similar to the seasonality effects you learned about in the previous chapter, Prophet contains default holidays that you can apply to your models, as well as custom holidays that you can create yourself. This chapter will cover both situations. Additionally, you will learn how...