LEADER 03402oam 2200481 450 001 9910822817603321 005 20210528112543.0 010 $a1-119-68238-X 010 $a1-119-68239-8 010 $a1-119-68237-1 035 $a(CKB)4100000011632866 035 $a(MiAaPQ)EBC6420045 035 $a(OCoLC-P)1226581333 035 $a(PPN)272709751 035 $a(CaSebORM)9781119682363 035 $a(OCoLC)1226581333 035 $a(EXLCZ)994100000011632866 100 $a20210528d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine learning for time series forecasting with Python /$fFrancesca Lazzeri 210 1$aIndianapolis, Indiana :$cWiley,$d[2021] 210 4$d©2021 215 $a1 online resource (227 pages) 311 $a1-119-68236-3 327 $aOverview of Time Series Forecasting -- How to Design an End-to-End Time Series Forecasting Solution on the Cloud -- Time Series Data Preparation -- Introduction to Autoregressive and Automated Methods for Time Series Forecasting -- Introduction to Neural Networks for Time Series Forecasting -- Model Deployment for Time Series Forecasting. 330 $aLearn how to apply the principles of machine learning to time series modeling with this indispensable resource 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. Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to: Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality Prepare time series data for modeling Evaluate time series forecasting models' performance and accuracy Understand when to use neural networks instead of traditional time series models in time series forecasting Machine Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling. 606 $aMachine learning 606 $aPython (Computer program language) 615 0$aMachine learning. 615 0$aPython (Computer program language) 676 $a006.31 700 $aLazzeri$b Francesca$0617825 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 906 $aBOOK 912 $a9910822817603321 996 $aMachine learning for time series forecasting with Python$94055511 997 $aUNINA