Machine Learning for Time Series Forecasting with Python

Learn how to apply the principles of machine learning to time series modeling with thisindispensableresource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-makingin finance,marketing,education, and healthcare:time series modeling. Despitethe 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 distinguishedmachine learning scientistandeconomist,corrects that deficiency by providing readers withcomprehensiveand approachableexplanation andtreatment of the applicationof machine learning to time series forecasting. Written for readers who have little to no experience in time seriesforecastingor machine learning, the book comprehensively coversall the topics necessary to: Understand time series forecasting concepts, such asstationarity,horizon,trend,and seasonality Prepare time

series dataformodeling Evaluatetime 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 fullreal-world examples, resourcesand 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. [Publisher's Text]

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