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SageWorks: An easy to use Python API for creating and deploying AWS SageMaker Models

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# Pull Request Checklist Thank you for contributing to the SuperCowPowers SageWorks project. Please make sure you've completed the following tasks before submitting your pull request: #### GENERAL - [x]...

We need to test out the API key functionality: - Expiration (Nice message when it expires) - Features Flags - Ensure AWS Account ID check

aws

So the addition of kwargs is a nice bit of flexibility so that plugins can can in additional information, but looks like we still have a wrinkle with the implementation....

bug
dash
plugins

Let's add a `set_input` part to model onboarding, also if we're in a situation where the FeatureSet doesn't exist we need to think of a marker/flag that means the model...

api
feature_set
model

Lets have the 'table' web_component have filters on by default.

web_interface
dash

Now that the model details markdown doesn't include model metrics (which is good), it can probably be more general. Right now it's a bit awkward when used in the Endpoint...

web_interface
application
dash

Right now the tag display on the Dashboard look 'not good'. So review how the dashboard is processing tags and make the display nicer. Tags: table:physchemproperty:processing:featurized:assay:solubility:feature_endpoint:smiles-to-rdkit-modred:date:2024_03_01

web_interface
feature_set
dash

The 'query' link for the datasets seems to work fine, but the query link for FeatureSets all say 'unknown'.

web_interface
data_source

Our test suite is giving deprecation warnings.. so run `tox` review the deprecation warnings and try to fix/address all of them.

ci_cd

After creating a DataSource with either a file or DataFrame input, have the ability to set an input 'path' (s3 whatever).

api
data_source