skforecast and pytorch-forecasting
These are **complements**: skforecast provides a unified interface for fitting various ML models (scikit-learn, XGBoost, LightGBM) to time series, while pytorch-forecasting offers deep learning architectures (LSTM, Transformer, etc.) that can be integrated into skforecast's pipeline for neural network-based forecasting.
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 pytorch-forecasting
sktime/pytorch-forecasting
Time series forecasting with PyTorch
This project helps data scientists and analysts forecast future trends using historical time series data. You input structured dataframes containing time series, and it outputs predictions for what will happen next. It's designed for professionals who need to predict demand, sales, resource utilization, or other time-dependent metrics.
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