MLOps with Azure ML

101601

Generalize model tag finder, tag model experiment_name (#103)

2.1.0 Update

There have been quite a few fixes and enhancements since the 2.0.0 release and want to summarize the changes here sorted by PR merge date.

Features:

1. Add support for scoring image using Web App for containers #54 @sudivate
2. Add support for Training R model code on ML Compute & Databricks #77 @eedorenko
3. Upgrade build train CI to use new multi-stage pipelines #90 @dtzar
4. Switch CI to use new Azure ML Agentless Task & improve/overhaul model evaluation, registration #101 @dtzar

Updates:

1. Register to use newer sdk method #65 @jpe316
2. Use Azure ML SDK more consistently #67 @tarockey
3. badge to proper AzDO repo & better pipeline filters #81 @dtzar
4. Enable App Insight by default on scoring image #86 @alla15747
5. Newest Conda dependencies for scoring images and project #93 @dtzar
6. Cleaner / Less variables including using AzDO variable template #99 @dariuszparys
7. Tag models with experiment name, filter models in evaluation via experiment name #103 @dtzar

Doc Enhancements:

1. Update to flow getting started #63 @omartin2010
2. Better getting started clarity #82 @Smarker

Fixes:

1. Authentication error fix #51 @eedorenko
2. Doc: Code description spelling fix #59 @tarockey
3. Doc: permissions fix #61 @sudivate
4. Doc: Readme typo fix #62 @Anand372
5. Doc: Fix typo #71 @Seddryck

MLOps with Azure ML

101373

Switch CI to use new AzureML agentless execution task (#101)

MLOps with Azure ML

101121

cleaner variables (#99)

MLOps with Azure ML

Update conda_dependencies (#95)

Adds back old PyPi package to fix the crash loop container for ACI/AKS deployments.

MLOps with Azure ML

Upgrade build train CI pipeline to multi-stage (#90)

* add staged pipeline

* remove release id

* remove train in release pipeline

* revert to BASE_NAME vars

* Move train trigger to new stage

* cleanup register comments

* add conditional for triggering train pipe

* update doc steps

* string vs boolean

* var to boolean

* set to false

* try with true

* cleanup images

* Use Coalesce so override works

* add back build artifacts

* address feedback

* include code/scoring path for ci

MLOps with Azure ML

update conda dependencies (#93)

* update dependencies

* cleanup spaces

MLOps with Azure ML

98627

enable App_Insight (#86)

MLOps with Azure ML

93791

Update getting started docs. (#82)

MLOps with Azure ML

Update Badge, Pipeline filters (#81)

* Update current build badge

* Only trigger Dockerfile change

* Include iac pr filter