This pull request fixes two issues and adds new functionality to the codebase. The first issue (#112) is related to the creation of the MachineLearning::Model::Registry class.
It allows tracking ML model deployment in stretchy apps.
The second issue (#113) involves the addition of rake tasks to manage indices, pipelines, and models. This pull request adds several rake tasks to perform various operations such as checking the status of indices, pipelines, and ML models, registering and deploying ML models, creating and deleting indices and pipelines, and more. These rake tasks provide convenient command-line tools for managing the Elasticsearch functionality in the codebase.
The commits included in this pull request are:
Fix #112 Create MachineLearning::Model::Registry
Fix #113 Add rake tasks to manage indices, pipelines and models
Please review the changes and let me know if any further modifications are required.
This pull request fixes two issues and adds new functionality to the codebase. The first issue (#112) is related to the creation of the
MachineLearning::Model::Registryclass.It allows tracking ML model deployment in stretchy apps.
The second issue (#113) involves the addition of rake tasks to manage indices, pipelines, and models. This pull request adds several rake tasks to perform various operations such as checking the status of indices, pipelines, and ML models, registering and deploying ML models, creating and deleting indices and pipelines, and more. These rake tasks provide convenient command-line tools for managing the Elasticsearch functionality in the codebase.
The commits included in this pull request are:
Fix #112 Create MachineLearning::Model::Registry
Fix #113 Add rake tasks to manage indices, pipelines and models
Please review the changes and let me know if any further modifications are required.