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Forecasting Time Series Data by Greg Rafferty (33 results)
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paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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paperback. Condition: 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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Forecasting Time Series Data with Facebook Prophet: Build, improve, and optimize time series forecasting models using the advanced forecasting tool
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
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Forecasting Time Series Data with Facebook Prophet : Build, Improve, and Optimize Time Series Forecasting Models Using the Advanced Forecasting Tool
Language: English
Published by Packt Publishing, Limited, 2021
ISBN 10: 1800568533 ISBN 13: 9781800568532
Condition: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
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Forecasting Time Series Data with Prophet - Second Edition: Build, improve, and optimize time series forecasting models using Meta's advanced forecast (Paperback or Softback)
Language: English
Published by Packt Publishing 3/31/2023, 2023
ISBN 10: 1837630410 ISBN 13: 9781837630417
Paperback or Softback. Condition: New. Forecasting Time Series Data with Prophet - Second Edition: Build, improve, and optimize time series forecasting models using Meta's advanced forecast. Book.
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Condition: 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.
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Forecasting Time Series Data with Prophet: Build, improve, and optimize time series forecasting models using Meta's advanced forecasting tool, 2nd Edition
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Forecasting Time Series Data with Facebook Prophet: Build, improve, and optimize time series forecasting models using the advanced forecasting tool
Language: English
Published by Packt Publishing, Limited, 2021
ISBN 10: 1800568533 ISBN 13: 9781800568532
Condition: New. pp. 270.
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Forecasting Time Series Data with Prophet - Second Edition: Build, improve, and optimize time series forecasting models using Meta's advanced forecast
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Forecasting Time Series Data with Facebook Prophet: Build, improve, and optimize time series forecasting models using the advanced forecasting tool
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Forecasting Time Series Data with Prophet - Second Edition: Build, improve, and optimize time series forecasting models using Meta's advanced forecast
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Forecasting Time Series Data with Prophet
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Forecasting Time Series Data with Facebook Prophet
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Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Forecasting Time Series Data with Facebook Prophet: Build, improve, and optimize time series forecasting models using the advanced forecasting tool
Language: English
Published by Packt Publishing, Limited, 2021
ISBN 10: 1800568533 ISBN 13: 9781800568532
Condition: New. Print on Demand pp. 270.
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Forecasting Time Series Data with Facebook Prophet: Build, improve, and optimize time series forecasting models using the advanced forecasting tool
Language: English
Published by Packt Publishing, Limited, 2021
ISBN 10: 1800568533 ISBN 13: 9781800568532
Condition: New. PRINT ON DEMAND pp. 270.
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Forecasting Time Series Data with Prophet -: Build, improve, and optimize time series forecasting models using the advanced forecasting tool
Language: English
Published by Packt Publishing Limited, 2023
ISBN 10: 1837630410 ISBN 13: 9781837630417
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 47.13
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Forecasting Time-Series Data with Facebook Prophet: Build, improve, and optimize time-series forecasting models using the advanced forecasting tool
Language: English
Published by Packt Publishing Limited, 2021
ISBN 10: 1800568533 ISBN 13: 9781800568532
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 54.13
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Create and improve fully automated forecasts for time series data with strong seasonal effects, holidays, and additional regressors using PythonPurchase of the print or Kindle book includes a free PDF Elektronisches BuchKey Features:Explore Prophet, the open source forecasting tool developed at Meta, to improve your forecastsCreate a forecast and run diagnostics to understand forecast qualityFine-tune models to achieve high performance and report this performance with concrete statisticsBook 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.What You Will Learn:Understand the mathematics behind Prophet's modelsBuild practical forecasting models from real datasets using PythonUnderstand the different modes of growth that time series often exhibitDiscover how to identify and deal with outliers in time series dataFind out how to control uncertainty intervals to provide percent confidence in your forecastsProductionalize your Prophet models to scale your work faster and more efficientlyWho this book is 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.
