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Model Management/deployment #523

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abramvandergeest opened this issue Dec 11, 2019 · 0 comments

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kind/enhancement machine-learning

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abramvandergeest commented Dec 11, 2019

Current behavior:
single model given for each ML inference activity.

Expected behavior:
Tooling to allow for Soft/hard roll over between models.
A way to have inference:

do percentages of times used for one model or another
allow multiple files be dropped and pick the newest

What is the motivation / use case for changing the behavior?

Eventually ML models get stale and must be retrained
A/B testing of models
slow transition between models

Additional information you deem important (e.g. I need this tomorrow):

abramvandergeest added kind/enhancement machine-learning labels

abramvandergeest assigned mellistibco, fm-tibco and abramvandergeest

abramvandergeest mentioned this issue

Pseudo A/b testing framework #524

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