Rafferty Forecasting Time Series Data with Prophet

Build, improve, and optimize time series forecasting models using Meta's advanced forecasting tool
2. Auflage 2023
ISBN: 978-1-83763-550-4
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 282 Seiten

No detailed description available for "Forecasting Time Series Data with Prophet".

Autoren/Hrsg.

Rafferty, Greg

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsprognose
• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

Table of Contents - The History and Development of Time Series Forecasting
- Getting Started with Prophet
- How Prophet Works
- Handling Non-Daily Data
- Working with Seasonality
- Forecasting Holiday Effects
- Controlling Growth Modes
- Influencing Trend Changepoints
- Including Additional Regressors
- Accounting for Outliers and Special Events
- Managing Uncertainty Intervals
- Performing Cross-Validation
- Evaluating Performance Metrics
- Productionalizing Prophet

Über Autor(innen)

Rafferty Greg:
Greg Rafferty is a data scientist at Google in San Francisco, California. With over a decade of experience, he has worked with many of the top firms in tech, including Facebook (Meta) 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.