Practical time series analysis prediction with statistics and machine learning
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis...
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media, Incorporated
2019.
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| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630773306719 |
Tabla de Contenidos:
- 1. Time Series: An Overview and a Quick History
- 2. Finding and Wrangling Time Series Data
- 3. Exploratory Data Analysis for Time Series
- 4. Simulating Time Series Data
- 5. Storing Temporal Data
- 6. Statistical Models for Time Series
- 7. State Space Models for Time Series
- 8. Generating and Selecting Features for a Time Series
- 9. Machine Learning for Time Series
- 10. Deep Learning for Time Series
- 11. Measuring Error
- 12. Performance Considerations in Fitting and Serving Time Series Models
- 13. Healthcare Applications
- 14. Financial Applications
- 15. Time Series for Government
- 16. Time Series Packages
- 17. Forecasts About Forecasting
