Learn how to apply the principles of machine learning to series modeling with this indispensable resource
Despite the centrality of series forecasting, few business analysts are familiar with the power or utility of applying machine learning to 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 series forecasting.

Written for readers who have little to no experience in series forecasting or machine learning, the book comprehensively covers all the topics necessary to:

Understand series forecasting concepts, such as stationarity, horizon, trend, and seasonality

Prepare series data for modeling

Evaluate series forecasting models' performance and accuracy

Understand when to use neural networks instead of traditional series models in series forecasting

Machine Learning for Series Forecasting with Python is full real-world examples, resources and concrete strats to help readers explore and transform data and develop usable, practical 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 series modeling.



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