[tony_bagnall]

hi, I dont want to enter a public discussion about the split of sktime, I fear the application of Godwin's law. A summary of the key points behind the split from my perspective are here https://github.com/aeon-toolkit/aeon/issues/456 the other sides view will no doubt be forthcoming. If you want to chat about it, join our slack and message me, I'm more than happy to help. How are we different? Well I think we can all live together, its open source, but from my perspective the priorities are 1. Align as closely as we can with sklearn, so as to make it completely intuitive how to use aeon if you know sklearn. 2. Focus on implementations of state of the art algorithms for time series machine learners and less on just wrapping other code. The goal is to reduce the lead time from publication of new ideas to widespread adoption 3. Documentation: make it good.

my interests primarily lie in classification, clustering and regression, but next year we are going into the forecasting world, plenty of exciting collaborations in the brew.

[fastasucan]

Its refreshing to see that classification is mentioned before forecasting. It has been a frustrating journey embarking on time series classification as it seems overlooked compared to forecasting. Will follow this project closely, and implement it in my next project!

[tony_bagnall]

time series classification is my primary research area :)