This Guidance shows how you can bring your own machine learning (ML) models into Amazon SageMaker Canvas and remove the need to manually change your code that is often required when building or moving ML models in new environments. In this Guidance, we showcase three patterns for how your teams can use ML models with SageMaker Canvas. One, you can register ML models in the SageMaker model registry, which is a metadata store for ML models. Two, you can directly share models built using Amazon SageMaker Autopilot. Three, you can use Amazon SageMaker Jumpstart and import the ML models into SageMaker Canvas. Business analysts can then analyze and generate predictions from any model in Canvas without writing a single line of code.