Open Source Time Series Ecosystem
Elevate your time series insights with state of the art fast and scalable implementations.
Time Series Ecosystem
Lightning fast forecasting with statistical and econometric models.
Scalable machine learning for time series forecasting.
Scalable and user friendly neural forecasting algorithms for time series data.
Probabilistic Hierarchical forecasting with statistical and econometric methods.
Calculates various features from time series data. Python implementation of the R package ts features.
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”
“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”
“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”
“The robust evaluation that the Nixtla team always follows is a testament to why the Nixtla team succeeds in building their tech stack”