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Key benefits

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

Description

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.

Who is this book for?

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.

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

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Colour book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Causal Inference and Discovery in Python

£40.99

Forecasting Time Series Data with Prophet

£33.99

Modern Time Series Forecasting with Python

£39.99

Total £ 114.97

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Amazon verified reviews

Riff Raff May 03, 2023

I’ve been looking for a book like this for years. Five stars!

Amazon Verified review

Cove R. May 12, 2023

The details in this second edition are incredibly helpful. This book is a complete upgrade with plenty of information on some of the advanced features that are hard to locate anywhere else. The new color charts and working examples make a big difference. This author knows his stuff and explains clearly and thoroughly. Valuable addition to the forecasting world!

Om S Apr 28, 2023

"Forecasting Time Series Data with Prophet" is a comprehensive guide for data scientists, machine learning engineers, and software engineers who want to build time-series forecasts using Python. The book focuses on Prophet, the open-source forecasting tool developed by Meta, and provides readers with a step-by-step approach to understanding and implementing Prophet's cutting-edge forecasting techniques.The book starts by tracing the evolution of time-series forecasting from basic early models to present-day advanced models. Readers then dive deep into the mathematics and theory behind Prophet, and learn how to build practical forecasting models from real datasets using Python. The author covers advanced features such as visualizing forecasts, adding holidays and trend changepoints, handling outliers, and modeling shocks such as COVID. Readers will also discover how to optimize more complicated models with hyperparameter tuning and additional regressors.The author provides concrete statistics to report the performance of the models, and readers will learn how to run diagnostics to evaluate the performance of their models. They will also discover useful features when running Prophet in production environments.Overall, "Forecasting Time Series Data with Prophet" is an excellent resource for anyone who wants to build scalable and accurate time-series models. The book is well-structured, and the explanations are clear and concise, making it easy for readers to understand the complex concepts involved. This book is recommended for business managers, data scientists, data analysts, and software engineers who want to build advanced forecasting models with concise, understandable, and repeatable code.

G Oct 11, 2024

I don't know who wrote this book but he must be a frigging genius. I've never before read anything so life-changing. If there were a Nobel Prize for excellence in how-to books about software development, this author would be a clear winner. I've heard rumors that he's also ravishingly handsome and could easily make a career as a professional model if he were so inclined.Full disclosure: I am the author of this book.

Yiqiao Yin Apr 08, 2023

Prophet is a powerful tool that empowers Python and R developers to construct scalable time series predictions. This guidebook will equip you with the necessary knowledge to implement Prophet's state-of-the-art forecasting techniques and model future data with a higher degree of accuracy and with minimal lines of code.You'll embark on a journey to explore the evolution of time series forecasting, from the rudimentary early models to the cutting-edge models of the present era. The book will guide you through the process of installing and configuring Prophet on your computer and building your initial model using just a few lines of code. You'll also delve into more advanced features, such as visualizing your forecasts, adding holidays, seasonality, and trend changepoints, handling outliers, and more. Additionally, you'll gain an understanding of why and how to modify each of the default parameters.As you progress through the later chapters, you'll learn how to optimize more complex models with hyperparameter tuning and by incorporating additional regressors into the model. Finally, you'll discover how to run diagnostics to evaluate the performance of your models and take advantage of some useful features when utilizing Prophet in production environments. By the end of this comprehensive Prophet book, you'll be able to take a raw time series dataset and develop advanced and precise forecasting models using concise, comprehensible, and replicable code.

Forecasting Time Series Data with Prophet: Build, improve, and optimize time series forecasting models using Meta's advanced forecasting tool , Second Edition

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