Open Source Time Series Ecosystem

Elevate your time series insights with state of the art fast and scalable implementations.

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Open source

Open Source
Time Series Ecosystem

StatsForecast

Lightning fast forecasting with statistical and econometric models.

MLForecast

Scalable machine learning for time series forecasting.

NeuralForecast

Scalable and user friendly neural forecasting algorithms for time series data.

Hierarchical Forecast

Probabilistic Hierarchical forecasting with statistical and econometric methods.

TS features

Calculates various features from time series data. Python implementation of the R package ts features.

Nixtla/Nixtla

Offers a collection of classes and methods to interact with the API of TimeGPT.

The most acknowledged figures in the field publicly endorse Nixtla

“The best python implementation of my methods are available from Nixtla”

Rob Hyndman

Monash University

“Nixtla is building time series forecasting tech the right way: focusing on evaluation/reproducibility, playing well with engineering systems, and providing a variety of options so users can choose the right tool for the job”

Sean Taylor

Creator of Facebook Prophet | Mofit Analytics

“Don’t waste time building time series models with complex and hard to use libraries and APIs. Check out the simple and super easy to use libraries from Nixtla”

Dipanjan Sakar

Google Developer Expert

“The robust evaluation that the Nixtla team always follows is a testament to why the Nixtla team succeeds in building their tech stack”

Valeriy Manokhin

Open Predictive Technologies