MLOps Quickstart #8462
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MLOps Quickstart #8462
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added 3 commits
May 9, 2023 08:53
Signed-off-by: Larry O’Brien <larry.obrien@databricks.com>
Signed-off-by: Larry O’Brien <larry.obrien@databricks.com>
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BenWilson2
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May 19, 2023
BenWilson2
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May 19, 2023
BenWilson2
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May 19, 2023
BenWilson2
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May 19, 2023
BenWilson2
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May 19, 2023
docs/source/_static/images/quickstart_mlops/register_model_button.png
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Co-authored-by: Ben Wilson <39283302+BenWilson2@users.noreply.github.com> Signed-off-by: Larry O'Brien <lobrien@knowing.net>
Signed-off-by: Larry O’Brien <larry.obrien@databricks.com>
Signed-off-by: Larry O’Brien <larry.obrien@databricks.com>
Signed-off-by: Larry O’Brien <larry.obrien@databricks.com>
Signed-off-by: Larry O’Brien <larry.obrien@databricks.com>
BenWilson2
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May 23, 2023
Searched for bad pattern, saw it in what-is-mflow.rst too Signed-off-by: Larry O’Brien <larry.obrien@databricks.com>
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Related Issues/PRs
Jira task DOC-8672
What changes are proposed in this pull request?
New MLOps-focused Quickstart
How is this patch tested?
Build in Sphinx, manual review
Does this PR change the documentation?
Release Notes
Is this a user-facing change?
New quickstart focused on MLops workflow: Review and select models, choose and register a model, serve a model, build a Docker container
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes