Author: Publisher:
ISBN:
Category : Biology
Languages : en
Pages : 326
Book Description
PROPHET Statistics
Author: Forecasting Time Series Data with Facebook Prophet
Author: Greg RaffertyPublisher: Packt Publishing Ltd
ISBN: 1800566522
Category : Computers
Languages : en
Pages : 270
Book Description
Create and improve high-quality automated forecasts for time series data that have strong seasonal effects, holidays, and additional regressors using Python Key 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 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. 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 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.
PROPHET Statistics
Author: Bolt, Beranek, and Newman, incPublisher:
ISBN:
Category : Biology
Languages : en
Pages :
Book Description
PROPHET: PROPHET statistics
Author: PROPHET Statistics
Author: Muhammad, Prophet of God
Author: Daniel C. PetersonPublisher: Wm. B. Eerdmans Publishing
ISBN: 0802807542
Category : Biography & Autobiography
Languages : en
Pages : 199
Book Description
Peterson engagingly tells the tale of this prophet, blending the texts of traditional sources into a clear narrative that opens a window on the life and influence of the first Muslim.
The Prophet
Author: Kahlil GibranPublisher:
ISBN:
Category : Mysticism
Languages : en
Pages : 132
Book Description
A Statistical Version of Prophet Inequalities
Author: David AssafForecasting Time Series Data with Prophet
Author: Greg RaffertyPublisher: Packt Publishing Ltd
ISBN: 1837635501
Category : Computers
Languages : en
Pages : 282
Book Description
Create and improve fully automated forecasts for time series data with strong seasonal effects, holidays, and additional regressors using Python Purchase of the print or Kindle book includes a free PDF eBook Key Features 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 Book DescriptionForecasting 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.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 Who this book is forThis 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.
Brigham Young
Author: John G. TurnerPublisher: Harvard University Press
ISBN: 0674067312
Category : Biography & Autobiography
Languages : en
Pages : 511
Book Description
Brigham Young was a rough-hewn New York craftsman whose impoverished life was electrified by the Mormon faith. Turner provides a fully realized portrait of this spiritual prophet, viewed by followers as a protector and by opponents as a heretic. His pioneering faith made a deep imprint on tens of thousands of lives in the American Mountain West.