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 1: The History and Development of Time Series Forecasting

Facebook Prophet is a powerful tool for creating, visualizing, and optimizing your forecasts! With Prophet, you'll be able to understand what factors will drive your future results and enable you to make more confident decisions. You'll accomplish these tasks and goals through an intuitive but very flexible programming interface that is designed for both the beginner and expert alike.

You don't need a deep knowledge of the math or statistics behind time series forecasting techniques to leverage the power of Prophet, although if you do possess this knowledge, Prophet includes a rich feature set that allows you to deploy your experience to great effect. You'll be working in a structured paradigm where each problem follows the same pattern, allowing you to spend less time figuring out how to optimize your forecast and more time discovering key insights to supercharge your decisions.

This chapter introduces the foundational ideas behind time series forecasting and discusses some of the key model iterations that eventually led to the development of Prophet. In this chapter, you'll learn what time series data is and why it must be handled differently than non-time series data, and then you'll discover the most powerful innovations, of which Prophet is the latest. Specifically, we will cover an overview of what time series forecasting is and then go into more detail on some specific approaches:

  • Understanding time series forecasting
  • Moving average and exponential smoothing
  • ARIMA
  • ARCH/GARCH
  • Neural networks
  • Prophet