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Time Series Forecasting in Python
€ 61,63
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Description
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:
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In Time Series Forecasting in Python you will learn how to:
- Recognize a time series forecasting problem and build a performant predictive model
- Create univariate forecasting models that account for seasonal effects and external var...
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:
Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You''ll explore interesting real-world datasets like Google''s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.
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In Time Series Forecasting in Python you will learn how to:
- Recognize a time series forecasting problem and build a performant predictive model
- Create univariate forecasting models that account for seasonal effects and external variables
- Build multivariate forecasting models to predict many time series at once
- Leverage large datasets by using deep learning for forecasting time series
- Automate the forecasting process
Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You''ll explore interesting real-world datasets like Google''s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.
Recensie
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Specifications
ISBN
9781617299889
Binding type
Paperback
Publication date
10 november 2022
Number of pages
456 pages
Dimensions
187 x 235 x 36 mm
Weight
848 grams
Publisher
Manning Publications
Edition
—
5% student discount
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