MLOpsPython

Microsoft ❤ MLOps release

There have been 33 PRs to master since the 2.2.0 release (sorry, we're not keeping up with semver). At this point there are several major changes to the repository since then which make it hard to simply upgrade and plenty of significant improvements to warrant 3.0. A big push was made to make it a better experience to bring your own ML project code based on usage from customers using this template for their production implementations.

Features:

• Add Build UI link as a tag so Azure ML pipeline runs can link back to Azure DevOps build which triggered the run #132 @jotaylo
• Added experimentation folder and Juypter notebooks for diabetes ridge regression model #145 @bjcmit
• Change folder structure to support multiple models and intellisense (code --> diabetes_regression) #147
  @sbaidachni
• Discover scoring model & add swagger endpoint to scoring container #149 @algattik
• Add toggle for evaluation step #152 @sudivate
• Always run Azure DevOps pipeline evaluation step to avoid confusion with cancellation #154 @jotaylo
• Add .amlignore example of usage #155 @sbaidachni
• Remove sys.path imports everywhere to support IntelliSense #162 @sbaidachni
• Add code coverage #150 @algattik
• Consistent manage environments in conda YML files #158, #168 @algattik
• Remove the pkl extension requirement for model name #164 @sbaidachni
• Support config file for code reference, switch alpha parameter from pipeline to config #169 @sbaidachni
• Fail when there is an error with R code #173 @algattik
• Add bootstrap code to more easily bring your own code #186 @sudivate
• Bootstrap code renames all instances of "diabetes" #189 @dtzar
• Bootstrap supports mac and linux machines #190 @eedorenko
• Modified to use dataset and pipelinedata #193 @GraemeMalcolm

Fixes:

• Doc: Clarifications in getting started #131 @jotaylo
• Build_uri assignment bug #133 @starlord-daniel
• extending use of SOURCES_DIR_TRAIN variable #143 & fix #146 @jotaylo
• pipeline with r name reference #167 @algattik
• sklearn joblib warning #174 @algattik
• Doc: link to point to not remove yml files #176 @timpoth
• ACI deployment #178 @sudivate
• Doc: links & typos #175 @eedorenko
• Add required azureml-dataprep package to deps #182 @eedorenko
• Rearrange & fix unit tests #184 @bjcmit
• Doc: clarifying comments #187 @eedorenko