Machine learning for time series forecasting with Python / Francesca Lazzeri
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TextPublication details: Hoboken : John Wiley & Sons, 2021Description: xviii, 206 pISBN: - 9781119682363
- 005.133 LAZ-M
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| Current library | Call number | Status | Barcode | |
|---|---|---|---|---|
| UMT Main Campus | 005.133 LAZ-M (Browse shelf(Opens below)) | Available | 152599 |
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| 005.133 LAN-D Data structures using C and C++ / | 005.133 LAN-D Data structures using C and C++ / | 005.133 LAN-S Standard C++ Iostreams and locales | 005.133 LAZ-M Machine learning for time series forecasting with Python / | 005.133 LEA-V Visual C++ 2.0 : A developer's guide | 005.133 LEE-C C++ programming for the absolute beginner/ | 005.133 LEE-C C++ programming for the absolute beginner/ |
Includes bibliographical references and index.
Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting. -- Provided by publisher
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