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

Adding custom seasonalities

So far, the only seasonalities we have worked with are the defaults in Prophet: yearly, weekly, and daily. But there is no reason to limit ourselves to these seasonalities. If your data contains a cycle that is either longer or shorter than the 365.25-day yearly cycle, the 7-day weekly cycle, or the 1-day daily cycle, Prophet makes it easy to model this seasonality yourself.

A great example of a non-standard seasonality is the 11-year cycle of sunspots. Sunspots are regions on the Sun's surface that temporarily exhibit a much-reduced temperature, and hence appear much darker, than surrounding areas.

Beginning in approximately 1609, Galileo Galilei began systematic observation of sunspots and over the last 400+ years, this phenomenon has been constantly recorded. In fact, sunspots represent the longest continuously recorded time series of any natural phenomenon. Through these observations, scientists have identified a quasi-periodic cycle of 11...