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Skforecast: time series forecasting with Python and Scikit-learn

ARIMA and SARIMAX models

Forecasting with gradient boosting: XGBoost, LightGBM and CatBoost

Modelling time series trend with tree based models

Forecasting electricity demand with Python

Forecasting web traffic with machine learning and Python

Bitcoin price prediction with Python

Prediction intervals in forecasting models

Multi-series forecasting

Reducing the influence of Covid-19 on time series forecasting models

Forecasting time series with missing values

Intermittent demand forecasting

Stacking ensemble of machine learning models to improve forecasting

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Skforecast: forecasting series temporales con Python y Scikit-learn

Modelos ARIMA y SARIMAX

Forecasting con gradient boosting: XGBoost, LightGBM y CatBoost

Modelar series temporales con tendencia utilizando modelos de árboles

Forecasting de la demanda eléctrica

Forecasting de las visitas a una página web

Predicción del precio de Bitcoin con Python

Workshop predicción de series temporales con machine learning Universidad de Deusto / Deustuko Unibertsitatea

Intervalos de predicción en modelos de forecasting

Multi-series forecasting

Predicción demanda intermitente