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Time Series for Data Scientists - Data Management, Description, Modeling and Forecasting (Hardcover)
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Time Series for Data Scientists - Data Management, Description, Modeling and Forecasting (Hardcover)
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Learn by doing with this user-friendly introduction to time series
data analysis in R. This book explores the intricacies of managing
and cleaning time series data of different sizes, scales and
granularity, data preparation for analysis and visualization, and
different approaches to classical and machine learning time series
modeling and forecasting. A range of pedagogical features support
students, including end-of-chapter exercises, problems, quizzes and
case studies. The case studies are designed to stretch the learner,
introducing larger data sets, enhanced data management skills, and
R packages and functions appropriate for real-world data analysis.
On top of providing commented R programs and data sets, the book's
companion website offers extra case studies, lecture slides, videos
and exercise solutions. Accessible to those with a basic background
in statistics and probability, this is an ideal hands-on text for
undergraduate and graduate students, as well as researchers in
data-rich disciplines
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