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

Building a simple model in Prophet

The longest record of direct measurements of CO2 in the atmosphere was started in March 1958 by Charles David Keeling of the Scripps Institution of Oceanography. Keeling was based in La Jolla, California, but had received permission from the National Oceanic and Atmospheric Administration (NOAA) to use their facility located two miles above sea level on the northern slope of Mauna Loa, a volcano on the island of Hawaii, to collect carbon dioxide samples. At that elevation, Keeling's measurements would be unaffected by local releases of CO2, such as from nearby factories.

In 1961, Keeling published the data he had collected thus far, establishing that there was strong seasonal variation in CO2 levels and that they were rising steadily, a trend that later became known as the Keeling Curve. By May 1974, the NOAA had begun their own parallel measurements and have continued since then. The Keeling Curve graph is as follows:

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