skforecast and scalecast
These are competitors offering overlapping functionality—both provide frameworks for applying machine learning models to time series forecasting—though skforecast has substantially larger adoption and scalecast appears positioned for practitioners seeking a more specialized or opinionated approach.
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.
About scalecast
mikekeith52/scalecast
The practitioner's forecasting library
This tool helps forecasters predict future values from time-based data. You input historical data points and their corresponding dates, and it outputs future forecasts along with evaluations of different forecasting models. It's designed for data analysts, researchers, or anyone needing to make accurate predictions from time series, especially when data is messy or complex.
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