{"library":"sagemaker-mlflow","type":"library","category":null,"description":"sagemaker-mlflow is an AWS plugin that enables MLflow to use SageMaker as its backend for experiment tracking, allowing users to leverage SageMaker's managed infrastructure for MLflow tracking servers and artifact storage. The current version is 0.2.0, with releases occurring as new features or bug fixes are introduced, typically driven by community contributions and AWS service enhancements.","language":"python","status":"active","version":"0.2.0","tags":["aws","sagemaker","mlflow","machine learning","experiment tracking","mle"],"install":[{"cmd":"pip install sagemaker-mlflow","imports":["import sagemaker_mlflow"]}],"homepage":"https://aws.amazon.com/sagemaker/","github":"https://github.com/aws/sagemaker-mlflow","docs":null,"changelog":null,"pypi":"https://pypi.org/project/sagemaker-mlflow/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":55,"avg_install_s":12.1,"avg_import_s":0.2,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/sagemaker-mlflow/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}