Hands-on time series analysis with r - 9781484259917 - hands-on time series analysis with python: from basics to bleeding edge techniques di vishwas, b v; patel, ashish (23 risultati)
Lingua: Inglese
Editore: Apress, 2020
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Lingua: Inglese
Editore: Apress, 2020
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Editore: Apress, 2020
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Lingua: Inglese
Editore: Apress, 2020
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Condizione: New. 2020. 1st ed. paperback. . . . . .
Lingua: Inglese
Editore: Apress, 2020
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Editore: Apress, 2020
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Editore: Apress, 2020
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Editore: Apress, 2020
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Condizione: New. 2020. 1st ed. paperback. . . . . . Books ship from the US and Ireland.
Lingua: Inglese
Editore: Apress, 2020
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 407 pages. 8.75x5.75x1.00 inches. In Stock.
Lingua: Inglese
Editore: APress, US, 2020
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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Paperback. Condizione: New. Learn the concepts of time series from traditional to bleeding-edge techniques. This book uses comprehensive examples to clearly illustrate statistical approaches and methods of analyzing time series data and its utilization in the real world. All the code is available in Jupyter notebooks.You'll beg…in by reviewing time series fundamentals, the structure of time series data, pre-processing, and how to craft the features through data wrangling. Next, you'll look at traditional time series techniques like ARMA, SARIMAX, VAR, and VARMA using trending framework like StatsModels and pmdarima. The book also explains building classification models using sktime, and covers advanced deep learning-based techniques like ANN, CNN, RNN, LSTM, GRU and Autoencoder to solve time series problem using Tensorflow. It concludes by explaining the popular framework fbprophet for modeling time series analysis. After reading Hands-On Time Series Analysis with Python, you'll be able to apply these new techniques in industries, such as oil and gas, robotics, manufacturing, government, banking, retail, healthcare, and more. What You'll Learn:· Explains basics to advanced concepts of time series· How to design, develop, train, and validate time-series methodologies· What are smoothing, ARMA, ARIMA, SARIMA,SRIMAX, VAR, VARMA techniques in time series and how to optimally tune parameters to yield best results· Learn how to leverage bleeding-edge techniques such as ANN, CNN, RNN, LSTM, GRU, Autoencoder to solve both Univariate and multivariate problems by using two types of data preparation methods for time series.· Univariate and multivariate problem solving using fbprophet. Who This Book Is ForData scientists, data analysts, financial analysts, and stock market researchers.
Lingua: Inglese
Editore: Apress 2020-08-25, 2020
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Da: Chiron Media, Wallingford, Regno UnitoChiron Media
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Paperback. Condizione: New.
Lingua: Inglese
Editore: Apress, 2020
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. pp. 364.
Lingua: Inglese
Editore: Apress, 2020
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Da: moluna, Greven, Germaniamoluna
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Condizione: New.
Altre immaginiLingua: Inglese
Editore: Apress, 2020
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Hands-on Time Series Analysis with Python | From Basics to Bleeding Edge Techniques | B V Vishwas (u. a.) | Taschenbuch | xvii | Englisch | 2020 | Apress | EAN 9781484259917 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[…dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: APress, US, 2020
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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Paperback. Condizione: New. Learn the concepts of time series from traditional to bleeding-edge techniques. This book uses comprehensive examples to clearly illustrate statistical approaches and methods of analyzing time series data and its utilization in the real world. All the code is available in Jupyter notebooks.You'll beg…in by reviewing time series fundamentals, the structure of time series data, pre-processing, and how to craft the features through data wrangling. Next, you'll look at traditional time series techniques like ARMA, SARIMAX, VAR, and VARMA using trending framework like StatsModels and pmdarima. The book also explains building classification models using sktime, and covers advanced deep learning-based techniques like ANN, CNN, RNN, LSTM, GRU and Autoencoder to solve time series problem using Tensorflow. It concludes by explaining the popular framework fbprophet for modeling time series analysis. After reading Hands-On Time Series Analysis with Python, you'll be able to apply these new techniques in industries, such as oil and gas, robotics, manufacturing, government, banking, retail, healthcare, and more. What You'll Learn:· Explains basics to advanced concepts of time series· How to design, develop, train, and validate time-series methodologies· What are smoothing, ARMA, ARIMA, SARIMA,SRIMAX, VAR, VARMA techniques in time series and how to optimally tune parameters to yield best results· Learn how to leverage bleeding-edge techniques such as ANN, CNN, RNN, LSTM, GRU, Autoencoder to solve both Univariate and multivariate problems by using two types of data preparation methods for time series.· Univariate and multivariate problem solving using fbprophet. Who This Book Is ForData scientists, data analysts, financial analysts, and stock market researchers.
Lingua: Inglese
Editore: Apress, 2020
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- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Apress Aug 2020, 2020
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Learn the concepts of time series from traditional to bleeding-edge techniques. This book uses comprehensive examples to clearly illustratestatistical approaches and methods of analyzing time series data and its utilization in the…real world. All the code is available in Jupyter not Elektronisches Buch.You'll begin by reviewing time series fundamentals, the structure of time series data, pre-processing, and how to craft the features through data wrangling. Next, you'll look at traditional time series techniques like ARMA, SARIMAX, VAR, and VARMA using trending framework like StatsModels and pmdarima.The book also explains building classification models using sktime, and covers advanced deep learning-based techniques like ANN, CNN, RNN, LSTM, GRU and Autoencoder to solve time series problem using Tensorflow. It concludes by explaining the popular framework fbprophet for modeling time series analysis. After reading Hands-On Time Series Analysis with Python, you'll be able to apply these new techniques in industries, such as oil and gas, robotics, manufacturing, government, banking, retail, healthcare, and more.What You'll Learn: Explains basics to advanced concepts of time series How to design, develop, train, and validate time-series methodologies What are smoothing, ARMA, ARIMA, SARIMA,SRIMAX, VAR, VARMAtechniques in time series and how to optimally tune parameters to yield best results Learn how to leverage bleeding-edge techniques such as ANN, CNN, RNN, LSTM, GRU, Autoencoder to solve both Univariate and multivariate problems by using two types of data preparation methods for time series. Univariate and multivariate problem solving using fbprophet. Who This Book Is ForData scientists, data analysts, financial analysts, and stock market researchers 428 pp. Englisch.
Lingua: Inglese
Editore: Apress, 2020
- Brossura
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 364.
Lingua: Inglese
Editore: Apress, 2020
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- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Learn the concepts of time series from traditional to bleeding-edge techniques. This book uses comprehensive examples to clearly illustratestatistical approaches and methods of analyzing time series data and its utilization in the real…world. All the code is available in Jupyter not Elektronisches Buch.You'll begin by reviewing time series fundamentals, the structure of time series data, pre-processing, and how to craft the features through data wrangling. Next, you'll look at traditional time series techniques like ARMA, SARIMAX, VAR, and VARMA using trending framework like StatsModels and pmdarima.The book also explains building classification models using sktime, and covers advanced deep learning-based techniques like ANN, CNN, RNN, LSTM, GRU and Autoencoder to solve time series problem using Tensorflow. It concludes by explaining the popular framework fbprophet for modeling time series analysis. After reading Hands-On Time Series Analysis with Python, you'll be able to apply these new techniques in industries, such as oil and gas, robotics, manufacturing, government, banking, retail, healthcare, and more.What You'll Learn: Explains basics to advanced concepts of time series How to design, develop, train, and validate time-series methodologies What are smoothing, ARMA, ARIMA, SARIMA,SRIMAX, VAR, VARMAtechniques in time series and how to optimally tune parameters to yield best results Learn how to leverage bleeding-edge techniques such as ANN, CNN, RNN, LSTM, GRU, Autoencoder to solve both Univariate and multivariate problems by using two types of data preparation methods for time series. Univariate and multivariate problem solving using fbprophet. Who This Book Is ForData scientists, data analysts, financial analysts, and stock market researchers.
Lingua: Inglese
Editore: Apress, 2020
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 83,46
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Condizione: New. PRINT ON DEMAND pp. 364.
Lingua: Inglese
Editore: Apress, Apress Aug 2020, 2020
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- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 58,84
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Learn the concepts of time series from traditional to bleeding-edge techniques. This book uses comprehensive examples to clearly illustrate statistical approaches and methods of analyzing time series data and its utilization in the rea…l world. All the code is available in Jupyter not Elektronisches Buch.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 428 pp. Englisch.
