Data Science for Supply Chain Forecasting - 5 Angebote vergleichen
| Preise | 2019 | 2020 | 2021 |
|---|---|---|---|
| Schnitt | € 40,84 | € 43,33 | € 42,99 |
| Nachfrage |
1
Data Science for Supply Chain Forecasting
EN PB NWISBN: 9783110671100 bzw. 3110671107, in Englisch, De Gruyter, Taschenbuch, neu.
Open source statistical toolkits have progressed tremendously over the last decade. In this book Nicolas Vandeput demonstrates that these toolkits are more than enough to address real-world forecasting challenges as found in supply chains.
Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting contends that a true scientific method that includes experimentation, observation and constant questioning must be applied to supply chain as well. The first part of the book is focused on statistical "traditional" models and the second on machine learning. The various chapters are focused either on forecast models or on new concepts (overfit, underfit, kpi, outliers). The book is full of python examples to show the reader how to apply these models him/herself.
This is a book for practitioners focusing on data science and machine learning and demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. Through its hands-on approach, it is accessible to a large audience of supply chain practitioners.
2
Data Science for Supply Chain Forecasting Nicolas Vandeput Author
~EN PB NWISBN: 9783110671100 bzw. 3110671107, vermutlich in Englisch, De Gruyter, Taschenbuch, neu.
Lieferung aus: Vereinigte Staaten von Amerika, plus shipping.
Open source statistical toolkits have progressed tremendously over the last decade. In this book Nicolas Vandeput demonstrates that these toolkits are more than enough to address real-world forecasting challenges as found in supply chains. Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting contends that a true scientific method that includes experimentation, observation and constant questioning must be applied to supply chain as well. The first part of the book is focused on statistical traditional models and the second on machine learning. The various chapters are focused either on forecast models or on new concepts (overfit, underfit, kpi, outliers). The book is full of python examples to show the reader how to apply these models him/herself. This is a book for practitioners focusing on data science and machine learning and demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. Through its hands-on approach, it is accessible to a large audience of supply chain practitioners.
Open source statistical toolkits have progressed tremendously over the last decade. In this book Nicolas Vandeput demonstrates that these toolkits are more than enough to address real-world forecasting challenges as found in supply chains. Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting contends that a true scientific method that includes experimentation, observation and constant questioning must be applied to supply chain as well. The first part of the book is focused on statistical traditional models and the second on machine learning. The various chapters are focused either on forecast models or on new concepts (overfit, underfit, kpi, outliers). The book is full of python examples to show the reader how to apply these models him/herself. This is a book for practitioners focusing on data science and machine learning and demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. Through its hands-on approach, it is accessible to a large audience of supply chain practitioners.
3
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Data Science for Supply Chain Forecasting
~EN PB NWISBN: 9783110671100 bzw. 3110671107, vermutlich in Englisch, De Gruyter, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Data Science for Supply Chain Forecasting: Open source statistical toolkits have progressed tremendously over the last decade. In this book Nicolas Vandeput demonstrates that these toolkits are more than enough to address real-world forecasting challenges as found in supply chains. Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting contends that a true scientific method that includes experimentation, observation and constant questioning must be applied to supply chain as well. The first part of the book is focused on statistical `traditional` models and the second on machine learning. The various chapters are focused either on forecast models or on new concepts (overfit, underfit, kpi, outliers). The book is full of python examples to show the reader how to apply these models him/herself. This is a book for practitioners focusing on data science and machine learning and demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. Through its hands-on approach, it is accessible to a large audience of supply chain practitioners. Englisch, Taschenbuch.
Data Science for Supply Chain Forecasting: Open source statistical toolkits have progressed tremendously over the last decade. In this book Nicolas Vandeput demonstrates that these toolkits are more than enough to address real-world forecasting challenges as found in supply chains. Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting contends that a true scientific method that includes experimentation, observation and constant questioning must be applied to supply chain as well. The first part of the book is focused on statistical `traditional` models and the second on machine learning. The various chapters are focused either on forecast models or on new concepts (overfit, underfit, kpi, outliers). The book is full of python examples to show the reader how to apply these models him/herself. This is a book for practitioners focusing on data science and machine learning and demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. Through its hands-on approach, it is accessible to a large audience of supply chain practitioners. Englisch, Taschenbuch.
4
Data Science for Supply Chain Forecasting
~EN PB NWISBN: 3110671107 bzw. 9783110671100, vermutlich in Englisch, Gruyter Walter de GmbH, Taschenbuch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
5
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Data Science for Supply Chain Forecasting
EN PB NW FEISBN: 9783110671100 bzw. 3110671107, in Englisch, 280 Seiten, De Gruyter, Taschenbuch, neu, Erstausgabe.
Lieferung aus: Deutschland, Noch nicht erschienen. Versandkostenfrei.
Von Händler/Antiquariat, Amazon.de.
Taschenbuch, Ausgabe: 1, Label: De Gruyter, De Gruyter, Produktgruppe: Book, Publiziert: 2020-01-20, Studio: De Gruyter.
Von Händler/Antiquariat, Amazon.de.
Taschenbuch, Ausgabe: 1, Label: De Gruyter, De Gruyter, Produktgruppe: Book, Publiziert: 2020-01-20, Studio: De Gruyter.
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