Difference between revisions of "MLflow"
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* [http://mlflow.org/ MLflow.org] | * [http://mlflow.org/ MLflow.org] | ||
* [http://github.com/mlflow/mlflow MLflow | GitHub] | * [http://github.com/mlflow/mlflow MLflow | GitHub] | ||
| + | * [[Development]] ... [[Development#AI Pair Programming Tools|AI Pair Programming Tools]] ... [[Analytics]] ... [[Visualization]] ... [[Diagrams for Business Analysis]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]] | ||
* [http://towardsdatascience.com/empowering-spark-with-mlflow-58e6eb5d85e8 Empowering Spark with MLflow | Albert Franzi - Towards Data Science] | * [http://towardsdatascience.com/empowering-spark-with-mlflow-58e6eb5d85e8 Empowering Spark with MLflow | Albert Franzi - Towards Data Science] | ||
* [http://www.kdnuggets.com/2018/07/manage-machine-learning-lifecycle-mlflow.html Manage your Machine Learning Lifecycle with MLflow] | * [http://www.kdnuggets.com/2018/07/manage-machine-learning-lifecycle-mlflow.html Manage your Machine Learning Lifecycle with MLflow] | ||
Revision as of 05:43, 2 July 2023
Youtube search... ...Google search
- MLflow.org
- MLflow | GitHub
- Development ... AI Pair Programming Tools ... Analytics ... Visualization ... Diagrams for Business Analysis ... AIOps/MLOps ... AIaaS/MLaaS
- Empowering Spark with MLflow | Albert Franzi - Towards Data Science
- Manage your Machine Learning Lifecycle with MLflow
- Databricks
MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility and deployment. It currently offers three components::
- Tracking — Record and query experiments: code, data, config, and results.
- Projects — Packaging format for reproducible runs on any platform.
- Models — General format for sending models to diverse deployment tools.
