AutoTS is an advanced Python library designed for automated forecasting of time series data at scale. It features dozens of statistical, machine learning, and deep learning models with scikit-learn style APIs, supports automated model selection and ensembling via AutoML, and handles both univariate and multivariate forecasting. With built-in tools for data transformation, probabilistic forecasting, scalability for thousands of series, and extensive options for model customization and evaluation, AutoTS is suitable for analysts, data scientists, and researchers who require high-accuracy time series forecasting for financial, commercial, or research purposes.
Visit Auto Ts's official website for product details and getting started.
Comprehensive API reference and usage examples for AutoTS.
Join the discussions and engage with other users of AutoTS on GitHub.