winedarksea/AutoTS

Health v2 · maintenance only

Adoption not part of the score

1430 stars · 122 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

AutoTS is a Python library for automated time series forecasting, offering dozens of sklearn-style models (statistical, ML, deep learning) plus 30+ time series transforms that operate directly on Pandas DataFrames. It includes an AutoML feature search using genetic algorithms to select models, preprocessing, and ensembles, with support for multivariate and probabilistic forecasts at scale.

Use cases

• forecast sales or demand across thousands of time series
• automatically find the best forecasting model for my dataset
• generate probabilistic upper and lower bound forecasts
• run an automl search over time series models and preprocessing
• forecast stock market or financial time series
• detect anomalies in time series data
• scale forecasting to hundreds of thousands of input series

When to choose

• you need automated, high-accuracy time series forecasting in Python with minimal manual tuning
• you work with Pandas DataFrames and want sklearn-style fit/predict APIs
• you need multivariate, probabilistic, or large-scale forecasting with ensembling

When to avoid

• you need general-purpose AutoML for non-time-series tabular data
• you need a forecasting service with a UI rather than a Python library
• you require real-time streaming forecasting rather than batch prediction

Facets

library · maturity active

machine-learning data-science etl machine-learning data-science time-series analytics python time-series forecasting automl sklearn-style genetic-algorithms probabilistic-forecasting anomaly-detection

Member repositories

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markdown · JSON · MCP: product_card(name="winedarksea/AutoTS")