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Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. In Time Series Forecasting in Python you will learn how to: Recognize a time series forecasting problem and build a perfor…
Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. In Time Series Forecasting in Python you will learn how to: Recognize a time series forecasting problem and build a perfor…
The book contains the most common as well as state-of-the-art methods in machine learning for time-series, and examples that every data scientist or analyst would have encountered, if not in their job, then in a job interview.
"Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding an…
Practical time series analysis using SAS
by Milhøj, Anders, SAS Institute
fromITPro collection
0
Type: Book
Time series data -- Datetime variables in SAS -- Aggregation using PROC TIMESERIES -- Interpolation using PROC EXPAND -- Exponential smoothing of nonseasonal series -- Forecasting by exponential smoothing of seasonal series -- Exponential smoothing versus parameterized models --…
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Anders Milhoj's "Practical Time Series Analysis Using SAS" explains and demonstrates through examples how you can use SAS for time series analysis. It offers modern procedures for forecasting, seasonal adjustments, and decomposition of time series that can be used without involv…
SAS/ETS 9.1: users' guide
0
Type: Book
SAS: users' guide
0
Type: Book
