sktime and skforecast
These are complementary tools: skforecast specializes in univariate and multivariate forecasting with a scikit-learn-compatible API, while sktime provides a broader unified framework for time series tasks (classification, regression, forecasting) that can incorporate skforecast's models as estimators within its pipelines.
About sktime
sktime/sktime
A unified framework for machine learning with time series
This tool helps you analyze time series data for various tasks like predicting future values, categorizing patterns, or detecting unusual shifts. You provide your historical data, and it outputs models that can make forecasts, classify new data, or identify anomalies. It's designed for data scientists, analysts, or researchers who work with sequential data over time.
About skforecast
skforecast/skforecast
Time series forecasting with machine learning models
This tool helps anyone who needs to predict future trends based on past data, such as sales managers, financial analysts, or operations planners. You input historical data, and it outputs predictions for what will happen next, like future sales or energy demand. It's designed for practitioners who want to use advanced machine learning for forecasting without needing to be an expert in every algorithm.
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