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Forecasting Time Series Data with Facebook Prophet
Forecasting Time Series Data with Facebook Prophet

Forecasting Time Series Data with Facebook Prophet: Build, improve, and optimize time series forecasting models using the advanced forecasting tool

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Profile Icon Greg Rafferty
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$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (17 Ratings)
Paperback Mar 2021 270 pages 1st Edition
eBook
$42.99
Paperback
$52.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Greg Rafferty
Arrow right icon
$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (17 Ratings)
Paperback Mar 2021 270 pages 1st Edition
eBook
$42.99
Paperback
$52.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$42.99
Paperback
$52.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • Learn how to use the open-source forecasting tool Facebook Prophet to improve your forecasts
  • Build a forecast and run diagnostics to understand forecast quality
  • Fine-tune models to achieve high performance, and report that performance with concrete statistics

Description

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.

Who is this book for?

This book is for data scientists, data analysts, machine learning engineers, software engineers, project managers, and business managers who want to build time series forecasts in Python. Working knowledge of Python and a basic understanding of forecasting principles and practices will be useful to apply the concepts covered in this book more easily.

What you will learn

  • Gain an understanding of time series forecasting, including its history, development, and uses
  • Understand how to install Prophet and its dependencies
  • Build practical forecasting models from real datasets using Python
  • Understand the Fourier series and learn how it models seasonality
  • Decide when to use additive and when to use multiplicative seasonality
  • Discover how to identify and deal with outliers in time series data
  • Run diagnostics to evaluate and compare the performance of your models

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 12, 2021
Length: 270 pages
Edition : 1st
Language : English
ISBN-13 : 9781800568532
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Facebook
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Product Details

Publication date : Mar 12, 2021
Length: 270 pages
Edition : 1st
Language : English
ISBN-13 : 9781800568532
Vendor :
Facebook
Category :
Languages :
Tools :

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Frequently bought together


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Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9
(17 Ratings)
5 star 88.2%
4 star 11.8%
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Luis Ek Mar 25, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Phenomenal book. A must read if you are a newbie in forecasting or you already using Facebook prophet in your forecasting suite system. The book starts off with a brief introduction to time series methods that are used across the forecasting domain. It provides the steps, with code, on how to get it running in your machine (OS or Windows), then goes into how to implement, debug it and even how to speed its process using parallelization techniques - (multi threading or dask). It is a perfect addition to the current product documentation.
Amazon Verified review Amazon
Amazon Customer Apr 21, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Forecasting Time Series Data with Facebook Prophet is a rather beginner-friendly book with hands-on code examples. It goes over the proper setup of Facebook Prophet in different OS, and how to deploy time-series models on data to yield results for further analysis. One thing I like about the content of this book is its elaboration on the input arguments to each time-series models in Prophet. For example, in the Seasonality chapter, the two options, ''multiplicative" vs. "additive'", for the seasonality_mode are elegantly discussed and moreover, I was able to grasp in an intuitive level when I should use "multiplicative", and when I should use "additive" by comparing the graphs the author provided in the chapter.The difficulty of the topics discussed in the book is structured sequentially from easy to hard, so as I was reading through the chapters without skipping any parts, I didn't encounter many difficulties in comprehending the analysis and technicality.Thus, I strongly recommend this book to time-series analysis beginners to gain some basic understanding of time-series analysis and Prophet implementation, as well as to mid-level readers for a knowledge refresh. One suggestion for the potential readers, if you are reading the electronic version, is to open two editors while reading the book, or put the book on both monitor screens, as some analysis on the graphs on the current page is served as a comparison to the graphs several pages ago or in the previous chapter. You might want to open two of the book so you know how the graph improves from the graph on a different page.
Amazon Verified review Amazon
Stacey H R May 03, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is clearly written and comprehensive. It provides end-to-end insight on time series analysis and how to best utilize Prophet. Whilst the Prophet documentation provides overviews and sample code, this book goes into much more detail explaining why you might want to use particular components and provides useful example data sets for hands-on experience for a range of scenarios. A great read!
Amazon Verified review Amazon
John Bowman Jan 09, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This e-book was well worth the $32 I paid. The writing is very clear with great examples. The e-book formatting is very good as well. I can use this content right away.
Amazon Verified review Amazon
A. Robertson Mar 16, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
An excellent and clear guide to FB Prophet. Excellent examples and good coding technique makes this a very useable book. Suitable for those with some basic knowledge of Pandas and Python as well as anyone looking to get good forecasts. Makes it much clearer than the product documentation (which is already pretty good).
Amazon Verified review Amazon
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