— Technology we master

Darts

The Python library that unifies time-series forecasting, from classic models to deep learning.

Darts, built by Unit8, exposes a single fit/predict API across dozens of forecasting models: ARIMA, Exponential Smoothing, Prophet and Theta, but also lag-based regression (LightGBM, XGBoost) and deep networks such as N-BEATS, TFT, TiDE or TSMixer. Its TimeSeries object handles multivariate series, past and future covariates, probabilistic forecasting, backtesting and anomaly detection. It's our choice when several model families need a fair comparison on the same series before the best one goes to production.

[ Why Darts ]

What Darts brings to your project.

Typical use cases: Sales and demand forecasting, inventory planning, energy consumption, capacity planning.

  1. 01

    Unified fit/predict API: ARIMA, Prophet, boosting and deep learning are interchangeable.

  2. 02

    Global models trained on thousands of series with past and future covariates.

  3. 03

    Probabilistic forecasting: quantiles and intervals to quantify uncertainty.

  4. 04

    Built-in backtesting and historical forecasts, plus an anomaly-detection module.

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A project with Darts?

Describe your project. Our team replies within 24 hours with free technical scoping, along with a clear estimate of costs and timelines. No commitment.

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