Kedro ML Framework
Open-source Python framework for creating reproducible, maintainable data science pipelines
Kedro ML Framework
Open-source Python framework for creating reproducible, maintainable data science pipelines
Kedro is an open-source Python framework from QuantumBlack (McKinsey) for creating reproducible, maintainable, and modular data science and ML pipelines. It applies software engineering best practices to data science by providing project templates, a data catalog abstraction, and pipeline visualization tools. Kedro encourages clean code organization, making ML projects more collaborative and production-ready. Data scientists and ML engineers transitioning from notebook-centric development to production codebases use Kedro to structure ML projects with engineering discipline.
Key Features
- ✓Pipeline framework
- ✓Data catalog
- ✓Project templates
- ✓Visualization
- ✓Open-source
Quick Info
- Category
- AI Infrastructure & MLOps
- Pricing
- Free
More AI Infrastructure & MLOps Tools
Dstack
AI Infrastructure & MLOpsOpen-source cloud-agnostic platform for AI/ML workload orchestration
Tigris Data
AI Infrastructure & MLOpsAI-native object storage with built-in vector search and S3 compatibility
Superlinked
AI Infrastructure & MLOpsVector compute framework that helps ML engineers build retrieval systems by combining multiple data types a…
Qdrant Cloud
AI Infrastructure & MLOpsManaged vector database cloud service offering high-performance similarity search with filtering, payload i…