an easy-to-use, easy-to-extend, comprehensive python framework for ML and AI with time series
open source, permissive license, free to use
openly and transparently governed by the user and developer community, with a charitable core
a friendly, responsive, kind and inclusive community, with an active commitment to fairness and equal opportunity
an academically, commercially neutral space, with an ecosystem integration ambition and neutral point of view
an educational platform, providing mentoring and upskilling for all career stages, especially early career
Our Roadmap describes how we try to achieve our mission.
Motivation: Why we develop sktime#
There are a number of reasons why we develop sktime, here are the most important ones:
Easier development of ML :term:`applications <application>` with time series, by making the ecosystem more interoperable and usable as a whole, and by providing an easy-to-use and readable way of specifying and applying algorithms.
Easier ML algorithm development, from research to implementation and testing.
Better ML algorithm research, by facilitating reproducibility and fair evaluation and comparison of different algorithms.
Easier teaching and learning for ML with time series.
Clearer time series methodology, especially more consistent definitions, terminology and notation across learning tasks.
More collaboration and innovation, by bringing together developers, practitioners and domain experts in a single project, by exploring a new community-driven model for the data science innovation cycle from methodology research to software development and deployment, and by offering alternative career paths for junior researchers and practitioners.