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<p><b>Learn how to apply the principles of machine learning to</b><b>time series modeling with this indispensable resource</b></p><p><i>Machine Learning for Time Series Forecasting with Python</i> 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.</p><p>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.</p><p>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:</p><ul><li>Understand time series forecasting concepts, such as stationarity, horizon,  trend, and seasonality</li><li>Prepare time series data for modeling</li><li>Evaluate time series forecasting models performance and accuracy</li><li>Understand when to use neural networks instead of traditional time series models in time series forecasting</li></ul><p><i>Machine Learning for Time Series Forecasting with Python</i>is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts.</p><p>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.</p><p></p><p></p>

Learn how to apply the principles of machine learning to&nbsp;time series modeling with this&nbsp;indispensable&nbsp;resource&nbsp; Machine Learning for Time Series Forecasting with Python&nbsp;is an incisive and straightforward examination of one of the most crucial elements of decision-making&nbsp;in finance,&nbsp;marketing,&nbsp;education, and healthcare:&nbsp;time series modeling.&nbsp;&nbsp; Despite&nbsp;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&nbsp;machine learning scientist&nbsp;and&nbsp;economist,&nbsp;corrects that deficiency by providing readers with&nbsp;comprehensive&nbsp;and approachable&nbsp;explanation and&nbsp;treatment of the application&nbsp;of machine learning to time series forecasting.&nbsp; Written for readers who have little to no experience in time series&nbsp;forecasting&nbsp;or machine learning, the book comprehensively covers&nbsp;all the topics necessary to:&nbsp; Understand time series forecasting concepts, such as&nbsp;stationarity,&nbsp;horizon,&nbsp;&nbsp;trend,&nbsp;and seasonality&nbsp;&nbsp; Prepare time series data&nbsp;for&nbsp;modeling&nbsp; Evaluate&nbsp;time series forecasting models&rsquo;&nbsp;performance and accuracy&nbsp; Understand when to use neural networks instead of traditional time series models in time series forecasting&nbsp; Machine Learning for Time Series Forecasting with Python&nbsp;is full&nbsp;real-world examples, resources&nbsp;and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts.&nbsp; Perfect for entry-level data scientists, business analysts,&nbsp;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.&nbsp; &nbsp; &nbsp;