Our great sponsors
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Kedro
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
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ML-airport-configuration
The ML-airport-configuration software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models intended for predicting airport configuration as a time series. The software is designed to point to databases which are not provided as part of the software release and thus this software is only intended to serve as an example of best practices. The software is built in python and leverages open-source libraries kedro, sc
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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https://github.com/nasa/ML-airport-configuration
Donation is the normal term for proejcts joining the foundation - in doing so you establish a steering committee where members are entitled to voting rights. To graduate as an incubation project, 5 organisations need to join your board and the project is thus the priorities of the project will no longer be driven by just one organisation.
In the short term there is still a full time internal team staffed and maintaining the project, but excitingly we now have a mechanism for new collaborators to properly come onboard.
Oooh, is that new? I have used Astral[0] in the last which worked well but required me to both define all my individual categories (no social/group suggested tags) and remember to use it every time I went on a starring spree.
This looks really interesting!
[0]: https://github.com/astralapp/astral
Really interesting response. While there's absolutely much to love about Kedro (we spoke to the core dev team - they're a fantastic bunch), we created Orchest to counter the cons you mentioned.
https://github.com/orchest/orchest
What do you think of Orchest? Given your unique perspective we'd love to hear what you think of it.
We've been having success with agencies, especially when the hand-off needs to be something the clients can easily run with.