Closed stichbury closed 1 year ago
Kedro is an open sourced Python framework for creating maintainable and modular data science code
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Kedro is a toolbox for production-ready data science.
Machine Learning Engineering Puts the "engineering" back into data science because it borrows concepts from software engineering and applies them to machine-learning code. It is the foundation for clean, data science code.
Can we make the first sentence a proper sentence?
Machine Learning Engineering Kedro is the foundation for clean, data science code. It borrows concepts from software engineering and applies them to machine-learning projects.
To make the change: Copy and replace text.
Handles Complexity Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardisation Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together. Production-Ready Makes a seamless transition from development to production, as you can write quick, throw-away exploratory code and transition to maintainable, easy-to-share, code experiments quickly.
Some changes to copy to make proper sentences as above.
Handles Complexity A Kedro project provides scaffolding for complex data and machine-learning pipelines. You spend less time on tedious "plumbing" and focus instead on solving new problems. Standardisation Kedro standardises how data science code is created, ensuring teams can collaborate to solve problems together. Production-Ready Make a seamless transition from development to production with throw-away exploratory code that you can transition to reproducible, maintainable, and modular experiments.
Integrations Apache Spark, Pandas, Dask, Matplotlib, Plotly, fsspec, Apache Airflow, Jupyter Notebook and Docker.
Should we add any of the following?
Note: We'd want their logos too
This is now done thanks to this PR
FAQs
You can find the Kedro community on Slack.
We also maintain a list of articles, podcasts, talks, and Kedro showcase projects in the kedro-community repository.
Change link
FAQs
You can find the Kedro community on Slack.
We also maintain a list of articles, podcasts, talks, and Kedro showcase projects in the awesome-kedro repository.
However, it would be great to add links here to the archives of discussions.
Change:
You can find the Kedro community on Slack.
To
You can find the Kedro community on Slack. Discussions from the Slack channels are also archived online, as are those from an earlier set of Discord channels.
This will help address https://github.com/kedro-org/kedro-devrel/issues/84
Ready to start? You are ready to get going with the Kedro workflow. But first, head to our documentation to learn how to install Kedro and then get up to speed with concepts like nodes, pipelines, the data catalog in our introductory tutorial.
Replace the copy
Ready to start? Visit the introductory tutorial to learn how to install Kedro and get up to speed with concepts like nodes, pipelines, and the data catalog.
@yetudada @astrojuanlu A few copy suggestions to update the website ahead of re-launch. I can collate all comments and build one single list of changes for the team to make.
I like the changes on this! I have two points:
FAQs
What is Kedro?
Kedro is an open-source Python framework hosted by the Linux Foundation (LF AI & Data). Kedro uses software engineering best practices to help you build production-ready data science code.
What's Kedro's origin story? Kedro was born at QuantumBlack to reduce technical debt in data science experiments, making an easier transition from experimentation to production. The latest iteration of Kedro is an incubating project within https://lfaidata.foundation/.
Closing this because I've created a final collated set of changes for the website here: https://github.com/kedro-org/kedro-website/issues/143
A small (I hope) task to review the website copy on the newly branded website in case any small tweaks would be beneficial at the time we make a new release. I'll create a set of suggestions here for signoff.