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
Kedro Plugin to support running workflows on GCP Vertex AI Pipelines
Wind Power Forecasting using Machine Learning techniques.
A kedro plugin to use pandera in your kedro projects
kedro cli plugin for generating a static kedro viz site (html, css, js) that can be deployed on many serverless tools.
Kedro Plugin to support running pipelines on Kubernetes using Airflow.
Create your own birdsong logger, powered by BirdNET-Tiny.
Find documentation and a template project for delivering Kedro training.
Anomaly Detection Pipeline with Isolation Forest model and Kedro framework
To associate your repository with the kedro topic, visit your repo's landing page and select "manage topics."