Conocer los fundamentos de las series temporales
Entrenar diferentes modelos estadísticos de series temporales como AR, MA, ARMA, ARIMA, SARIMA
Predecir datos futuros en base a series de tiempo
Proyecto aplicado y práctico para aprender a entrenar modelos de Machine Learning como: AR, MA, ARMA, ARIMA, autoARIMA, SARIMA y autoSARIMA para predecir series temporales con Python.
ARMA
Machine Learning
Autoregressive Integrated Moving Average (ARIMA)
Time Series
SARIMA
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introducción a las series temporales
Tipos de datos de series temporales
Preprocesamiento y análisis de series temporales
Ejercicio aplicado. Preprocesamiento y análisis
Técnicas para transformar series en estacionarias
Modelo de autoregresión (AR) y métricas de evaluación
Ejercicio aplicado. Modelo AR
Modelo de media móvil (MA) y media móvil autorregresiva (ARMA)
Ejercicio aplicado MA y ARMA
Modelo de ARIMA y autoARIMA
Modelo de SARIMA y auto SARIMA
Ejercicio aplicado. ARIMA y SARIMA
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
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