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.

Репозиторий для открытого курса «Промышленная эксплуатация моделей машинного обучения»

First-party plugins maintained by the Kedro team.

Templates for your Kedro projects.

Plugins, extensions, case studies, articles, and video tutorials for Kedro

Kedro Plugin to support running workflows on Kubeflow Pipelines

Kedro plugin to support running workflows on Microsoft Azure ML 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

A kedro plugin to use pandera in your kedro projects

Kedro Plugin to support running workflows on GCP Vertex AI Pipelines

Using ChatGPT to build a Kedro ML pipeline and Streamlit frontend

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.

Anomaly Detection Pipeline with Isolation Forest model and Kedro framework

It's the Complete Beginner's Guide to Kedro! See the video here: https://youtu.be/x97ChYDd12U