Forecasting Time Series Data with Prophet

Forecasting Time Series Data with Prophet will help you to implement Prophet's cutting-edge forecasting techniques to model future data with high accuracy using only a few lines of code. This second edition has been fully revised with every update to the Prophet package since the first edition was published two years ago. An entirely new chapter is also included, diving into the mathematical equations behind Prophet's models. Additionally, the book contains new sections on forecasting during shocks such as COVID, creating custom trend modes from scratch, and a discussion of recent developments in the open-source forecasting community.
You'll cover advanced features such as visualizing forecasts, adding holidays and trend changepoints, and handling outliers. You'll use the Fourier series to model seasonality, learn how to choose between an additive and multiplicative model, and understand when to modify each model parameter. Later, you'll see 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 in production.
By the end of this book, you'll be able to take a raw time series dataset and build advanced and accurate forecasting models with concise, understandable, and repeatable code.

Type
ebook
Category
publication date
2023-03-31
what you will learn

Understand the mathematics behind Prophet’s models
Build practical forecasting models from real datasets using Python
Understand the different modes of growth that time series often exhibit
Discover how to identify and deal with outliers in time series data
Find out how to control uncertainty intervals to provide percent confidence in your forecasts
Productionalize your Prophet models to scale your work faster and more efficiently

no of pages
282
duration
564
key features
Explore Prophet, the open source forecasting tool developed at Meta, to improve your forecasts * Create a forecast and run diagnostics to understand forecast quality * Fine-tune models to achieve high performance and report this performance with concrete statistics
approach
A hands-on approach to get up to speed and well-versed with Prophet to build, improve, and scale forecasting models.
audience
This book is for business managers, data scientists, data analysts, machine learning engineers, and software engineers who want to build time-series forecasts in Python or R. To get the most out of this book, you should have a basic understanding of time series data and be able to differentiate it from other types of data. Basic knowledge of forecasting techniques is a plus.
meta description
Create and improve fully automated forecasts for time series data with strong seasonal effects, holidays, and additional regressors using Python
Purchase of the print or Kindle book includes a free PDF eBook
short description
This book will help you get to grips with time series forecasting using the leading open source forecasting tool, Prophet. You’ll learn how to implement Prophet’s advanced features to build forecasting models and understand why and how to modify each of the default parameters to improve results.
subtitle
Build, improve, and optimize time series forecasting models using Meta's advanced forecasting tool
keywords
Python programming; python for data analysis; code book; R programming; coding; data analyst; data scientist
Product ISBN
9781837630417