Time series analysis with Python cookbook practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation
Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms Learn different techniques for evaluating, diagnosing, and opti...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, England ; Mumbai :
Packt
[2022]
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009669522406719 |
Tabla de Contenidos:
- Table of Contents Getting Started with Time Series Analysis Reading Time Series Data from Files Reading Time Series Data from Databases Persisting Time Series Data to Files Persisting Time Series Data to Databases Working with Date and Time in Python Handling Missing Data Outlier Detection Using Statistical Methods Exploratory Data Analysis and Diagnosis Building Univariate Time Series Models Using Statistical Methods Additional Statistical Modeling Techniques for Time Series Forecasting Using Supervised Machine Learning Deep Learning for Time Series Forecasting Outlier Detection Using Unsupervised Machine Learning Advanced Techniques for Complex Time Series.
