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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Updated
May 17, 2024 - Python
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.
Visualise your Kedro data and machine-learning pipelines and track your experiments.
A kedro-plugin for integration of mlflow capabilities inside kedro projects (especially machine learning model versioning and packaging)
Examples of data science projects created with Kedro.
First-party plugins maintained by the Kedro team.
Plugins, extensions, case studies, articles, and video tutorials for Kedro
Kedro Plugin to support running workflows on Kubeflow Pipelines
A tutorial on how to use kedro-mlflow plugin (https://github.com/Galileo-Galilei/kedro-mlflow) to synchronize training and inference and serve kedro pipeline
Kedro plugin to support running workflows on Microsoft Azure ML Pipelines
A kedro plugin to use pandera in your kedro projects
Kedro Plugin to support running workflows on GCP Vertex AI Pipelines
Kedro Plugin to support running pipelines on Kubernetes using Airflow.
kedro cli plugin for generating a static kedro viz site (html, css, js) that can be deployed on many serverless tools.
Find documentation and a template project for delivering Kedro training.
Wind Power Forecasting using Machine Learning techniques.
It's the Complete Beginner's Guide to Kedro! See the video here: https://youtu.be/x97ChYDd12U
Kedro Wings automatically creates catalog entries to simplify Kedro pipeline writing. See the video here: https://www.youtube.com/watch?v=p4ELo1tqbYY
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To associate your repository with the kedro topic, visit your repo's landing page and select "manage topics."