You're reading from Forecasting Time Series Data with Facebook Prophet

Product typeBook

Published inMar 2021

Reading LevelBeginner

PublisherPackt

ISBN-139781800568532

Edition1st Edition

Languages

Python

Tools

Prophet

Concepts

Predictive Analytics

Author (1)

Greg Rafferty

Section 2: Seasonality, Tuning, and Advanced Features

This section will teach you about the advanced features of Prophet. Every adjustable parameter will be explored with examples and a discussion of why and how to modify them. Each chapter builds on the previous chapters to add more and more complexity and power to the forecasting models. By the end of the section, you will be able to build models that harness the full capability of Prophet's forecasting toolset.

This section comprises the following chapters:

Chapter 3, Non-Daily Data
Chapter 4, Seasonality
Chapter 5, Holidays
Chapter 6, Growth Modes
Chapter 7, Trend Changepoints
Chapter 8, Additional Regressors
Chapter 9, Outliers and Special Events
Chapter 10, Uncertainty Intervals

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Author (1)

Greg Rafferty

Greg Rafferty is a data scientist in San Francisco, California. With over a decade of experience, he has worked with many of the top firms in tech, including Google, Facebook, and IBM. Greg has been an instructor in business analytics on Coursera and has led face-to-face workshops with industry professionals in data science and analytics. With both an MBA and a degree in engineering, he is able to work across the spectrum of data science and communicate with both technical experts and non-technical consumers of data alike.
Read more about Greg Rafferty

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