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  • Forecasting Time Series Data with Facebook Prophet: Build, improve, and optimize

    • Item No : 157010776070
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      Forecasting Time Series Data with Facebook Prophet

      by Greg Rafferty

      This book will help you get to grips with the task of time series forecasting using the leading open source forecasting tool available to the public, Facebook Prophet. You will learn how to implement the advanced features of Prophet to build forecast models and understand why and how to modify each of the default parameters to improve results.

      FORMAT
      Paperback
      LANGUAGE
      English
      CONDITION
      Brand New


      Publisher Description

      Create and improve high-quality automated forecasts for time series data that have strong seasonal effects, holidays, and additional regressors using PythonKey Features

      • 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
      Book DescriptionProphet 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 fi rst 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.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
      Who this book is forThis 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.

      Table of Contents

      Table of Contents

    • The History and Development of Time Series Forecasting
    • Getting Started with Facebook Prophet
    • Non-Daily Data
    • Seasonality
    • Holidays
    • Growth Modes
    • Trend Changepoints
    • Additional Regressors
    • Outliers and Special Events
    • Uncertainty Intervals
    • Cross-Validation
    • Performance Metrics
    • Productionalizing Prophet
    • Details

      ISBN1800568533
      Author Greg Rafferty
      Short Title Forecasting Time Series Data with Facebook Prophet
      Pages 270
      Language English
      Year 2021
      ISBN-10 1800568533
      ISBN-13 9781800568532
      Format Paperback
      Publisher Packt Publishing Limited
      Imprint Packt Publishing Limited
      Place of Publication Birmingham
      Country of Publication United Kingdom
      AU Release Date 2021-03-05
      NZ Release Date 2021-03-05
      Publication Date 2021-03-05
      Subtitle Build, improve, and optimize time series forecasting models using the advanced forecasting tool
      DEWEY 006.754
      Audience General
      UK Release Date 2021-03-05
      Replaced by 9781837630417

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