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Añadir al carritopaperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Añadir al carritoCondición: Gut. 270 S. Einband mit leichten Gebrauchsspuren, an Ecken leicht berieben. Seiten sauber. 383 Sprache: Englisch Gewicht in Gramm: 520 Taschenbuch, Maße: 23.5 cm x 19.05 cm x 1.45 cm.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por Packt Publishing 2021-03, 2021
ISBN 10: 1800568533 ISBN 13: 9781800568532
Librería: Chiron Media, Wallingford, Reino Unido
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Añadir al carritoPF. Condición: New.
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Añadir al carritoCondición: New. 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.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Idioma: Inglés
Publicado por Packt Publishing Limited, 2021
ISBN 10: 1800568533 ISBN 13: 9781800568532
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Create and improve high-quality automated forecasts for time series data that have strong seasonal effects, holidays, and additional regressors using PythonKey FeaturesLearn how to use the open-source forecasting tool Facebook Prophet to improve your forecastsBuild a forecast and run diagnostics to understand forecast qualityFine-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 LearnGain an understanding of time series forecasting, including its history, development, and usesUnderstand how to install Prophet and its dependenciesBuild practical forecasting models from real datasets using PythonUnderstand the Fourier series and learn how it models seasonalityDecide when to use additive and when to use multiplicative seasonalityDiscover how to identify and deal with outliers in time series dataRun 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.
Librería: preigu, Osnabrück, Alemania
EUR 65,50
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Añadir al carritoTaschenbuch. Condición: Neu. Forecasting Time Series Data with Facebook Prophet | Build, improve, and optimize time series forecasting models using the advanced forecasting tool | Greg Rafferty | Taschenbuch | Kartoniert / Broschiert | Englisch | 2021 | Packt Publishing | EAN 9781800568532 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.