Version 0.12.0 of the skforecast Python library for time series forecasting with regression models was released this week. The release includes new features, updates for existing ones, and bug fixes. 🧵👇🏼
(2/2) Here are some of the new features:
✅ Ability to forecast multiple series with different lengths and/or different exogenous variables per series.
✅ Bayesian hyperparameter search is now available for all multiseries forecasters using optuna as the search engine.
✅ New forecasting models based on deep learning models (RNN and LSTM)
✅ New methods for creating prediction intervals
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