Imagen 1 de 1
Imagen 1 de 1
Previsión de datos de series temporales con Facebook Prophet: construir, mejorar y optimizar,-
USD24,99
Aproximadamente23,09 EUR
Estado:
“Used book in good condition. Shows typical wear. Quick shipping. Satisfaction guaranteed!”
- ¡Cómpralo ya!Previsión de datos de series temporales con Facebook Prophet: construir, mejorar y optimizar,
Envío:
Ubicado en: Multiple Locations, Estados Unidos
Entrega:
Entrega prevista entre el mié. 7 ago. y el lun. 12 ago. a 84606
Devoluciones:
30 días para devoluciones. El comprador paga el envío de la devolución. Ver detalles- Más información sobre devoluciones
Pagos:
Compra con confianza
El vendedor asume toda la responsabilidad de este anuncio.
N.º de artículo de eBay:145806892435
Última actualización el 31 jul 2024 18:56:06 H.EspVer todas las actualizacionesVer todas las actualizaciones
Características del artículo
- Estado
- En buen estado
- Notas del vendedor
- “Used book in good condition. Shows typical wear. Quick shipping. Satisfaction guaranteed!”
- ISBN
- 9781800568532
- Publication Year
- 2021
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Subject Area
- Computers, Technology & Engineering
- Publication Name
- Forecasting Time Series Data with Facebook Prophet : Build, Improve, and Optimize Time Series Forecasting Models Using the Advanced Forecasting Tool
- Publisher
- Packt Publishing, The Limited
- Subject
- Engineering (General), Machine Theory, Neural Networks, Data Processing
- Number of Pages
- 270 Pages
Acerca de este producto
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1800568533
ISBN-13
9781800568532
eBay Product ID (ePID)
11050393299
Product Key Features
Subject
Engineering (General), Machine Theory, Neural Networks, Data Processing
Publication Year
2021
Number of Pages
270 Pages
Publication Name
Forecasting Time Series Data with Facebook Prophet : Build, Improve, and Optimize Time Series Forecasting Models Using the Advanced Forecasting Tool
Language
English
Type
Textbook
Subject Area
Computers, Technology & Engineering
Format
Trade Paperback
Additional Product Features
Dewey Edition
23
Dewey Decimal
006.754
Synopsis
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 statisticsBook 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 modelsWho 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., 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 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 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.
LC Classification Number
TK5105.88817
ebay_catalog_id
4
Descripción del artículo del vendedor
El vendedor asume toda la responsabilidad de este anuncio.
N.º de artículo de eBay:145806892435
Última actualización el 31 jul 2024 18:56:06 H.EspVer todas las actualizacionesVer todas las actualizaciones
Envío y manipulación
Ubicación del artículo:
Multiple Locations, Estados Unidos
Realiza envíos a:
Afganistán, Albania, Alemania, Andorra, Angola, Anguila, Antigua y Barbuda, Arabia Saudí, Argelia, Argentina, Armenia, Aruba, Australia, Austria, Azerbaiyán, Bahamas, Bahréin, Bangladés, Belice, Benín, Bermudas, Bolivia, Bosnia-Herzegovina, Botsuana, Brunéi, Bulgaria, Burkina Faso, Burundi, Bután, Bélgica, Cabo Verde, Camboya, Camerún, Canadá, Chad, Chile, China, Chipre, Colombia, Corea del Sur, Costa Rica, Costa de Marfil, Dinamarca, Ecuador, Egipto, El Salvador, Emiratos Árabes Unidos, Eritrea, Eslovaquia, Eslovenia, España, Estados Unidos, Estonia, Etiopía, Fiji, Filipinas, Finlandia, Francia, Gabón, Gambia, Georgia, Ghana, Gibraltar, Granada, Grecia, Groenlandia, Guatemala, Guinea, Guinea Ecuatorial, Guinea-Bisáu, Guyana, Haití, Honduras, Hong Kong, Hungría, India, Indonesia, Irlanda, Islandia, Islas Caimán, Islas Salomón, Islas Turcas y Caicos, Israel, Italia, Jamaica, Japón, Jordania, Kazajistán, Kenia, Kirguistán, Kiribati, Kuwait, Laos, Lesoto, Letonia, Liberia, Liechtenstein, Lituania, Luxemburgo, Líbano, Macao, Macedonia, Madagascar, Malasia, Malaui, Maldivas, Malta, Malí, Marruecos, Mauricio, Mauritania, Moldavia, Mongolia, Montenegro, Montserrat, Mozambique, México, Mónaco, Namibia, Nauru, Nepal, Nicaragua, Nigeria, Noruega, Nueva Zelanda, Níger, Omán, Pakistán, Panamá, Papúa Nueva Guinea, Paraguay, Países Bajos, Perú, Polonia, Portugal, Qatar, Reino Unido, República Centroafricana, República Checa, República Democrática del Congo, República Dominicana, República de Croacia, República del Congo, Ruanda, Rumanía, Samoa, San Cristóbal y Nieves, San Marino, San Vicente y las Granadinas, Santa Lucía, Senegal, Serbia, Seychelles, Sierra Leona, Singapur, Sri Lanka, Suazilandia, Suecia, Suiza, Surinam, Tailandia, Taiwán, Tanzania, Tayikistán, Togo, Tonga, Trinidad y Tobago, Turkmenistán, Turquía, Túnez, Uganda, Uruguay, Uzbekistán, Vanuatu, Vaticano, Vietnam, Wallis y Futuna, Yemen, Yibuti, Zambia, Zimbabue
Excluye:
Barbados, Federación Rusa, Guadalupe, Guayana Francesa, Libia, Martinica, Nueva Caledonia, Polinesia Francesa, Reunión, Ucrania, Venezuela
| Envío y manipulación | A | Servicio | Entrega*Consulta las notas de entrega |
|---|---|---|---|
| USD9,99 (aprox. 9,23 EUR) | Estados Unidos | Envío Económico (USPS Media MailTM) | Entrega prevista entre el mié. 7 ago. y el lun. 12 ago. a 84606 |
| USD19,99 (aprox. 18,47 EUR) | Estados Unidos | Expedited Shipping | Entrega prevista entre el mar. 6 ago. y el sáb. 10 ago. a 84606 |
| Tiempo de manipulación |
|---|
| Normalmente, se enviará en un plazo de 3 días laborables desde que se haga efectivo el pago. |
| Impuestos |
|---|
| Puede que se apliquen impuestos durante el pago y envío. Más informaciónMás información sobre el pago de impuestos en las compras de eBay. |
Impuesto de ventas del artículo 145806892435
Impuesto de ventas del artículo 145806892435
El vendedor carga un impuesto de ventas por los artículos enviados a los siguientes estados:
| Estado o provincia | Porcentaje de impuesto de ventas |
|---|
Política de devoluciones
| Cuando recibas el artículo, ponte en contacto con el vendedor en un plazo de | Forma del reembolso | Gastos de envío de la devolución |
|---|---|---|
| 30 días | Reembolso del dinero | El comprador paga el envío de la devolución |
Pulsa aquíaquí para obtener más información sobre devoluciones. En las transacciones que cumplan los requisitos necesarios, estarás cubierto por la Garantía al cliente de eBay si recibiste un artículo que es distinto de la descripción que aparece en el anuncio.
El comprador es responsable de los gastos de envío de la devolución.
| Detalles de la política de devoluciones |
|---|
| Se aceptan devoluciones |
Detalles de pago
Formas de pago
Nota: como resultado de la valoración de riesgo del comprador, es posible que algunas formas de pago no estén disponibles en el proceso de Pago y envío.
Registrado como vendedor profesional
Votos de vendedor (798)
m***s (78)- Votos emitidos por el comprador.
Mes pasado
Compra verificada
Do not buy this. Does not come with dust jacket and condition is very poor not good as stated. ThriftBooks disappoints once again
2***5 (581)- Votos emitidos por el comprador.
Mes pasado
Compra verificada
Purchase went well, book arrived in excellent condition
a***_ (8)- Votos emitidos por el comprador.
Mes pasado
Compra verificada
Thank you! :)