mlforecast
A Python framework for scalable time series forecasting using machine learning models, designed for production environments.
What is mlforecast?
mlforecast is a Python framework for time series forecasting using machine learning models. It provides fast feature engineering and scalable training to handle massive datasets, addressing the speed and accuracy limitations of existing tools. The framework is designed for production environments, supporting distributed computing backends like Dask, Ray, and Spark.
Data scientists and ML engineers working on time series forecasting projects that require scalability, performance, and integration with standard ML libraries like scikit-learn.
Developers choose mlforecast for its exceptional speed in feature engineering, seamless scalability to clusters, and familiar scikit-learn API, making it ideal for production forecasting tasks across large numbers of time series.
Overview
Scalable machine 🤖 learning for time series forecasting.
Use Cases
Best For
- Forecasting millions of time series efficiently in production
- Integrating machine learning models into time series workflows
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