mlforecast and skforecast
These are **competitors**: both provide end-to-end ML-based time series forecasting pipelines with similar core functionality (feature engineering, model training, backtesting), though mlforecast emphasizes distributed scalability while skforecast emphasizes scikit-learn model compatibility.
About mlforecast
Nixtla/mlforecast
Scalable machine 🤖 learning for time series forecasting.
This tool helps businesses and analysts predict future trends using historical time series data. You input multiple series of past observations, like sales figures or stock prices, and it outputs predictions for future values. It's designed for data scientists, operations managers, and anyone needing accurate, scalable forecasts for business planning or resource allocation.
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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