Deploying and Maintaining Models

Validate an incoming numerical batch

BOTIE

Send the table through the finite-width validator, then calculate its column means to confirm the same accepted values pass through.
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0 passed · 0 failed · 2 not run

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Context for this challenge

Send the table through the finite-width validator, then calculate its column means to confirm the same accepted values pass through.

Before applying a saved predictor, Botie needs a numerical batch with the declared width and finite entries.

Pass the input table through the finite-width validator, then calculate column means from the accepted values.

Examples and results
Input records
12
34
Required feature count
2
Required result
  1. 02
  2. 13
Input records
57
Required feature count
2
Required result
  1. 05
  2. 17
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Stuck? Inspect a worked construction

The tools below form one possible solution. You can assemble it, follow its signals, and undo that change to return to your own construction.

Assumptions and test precision

This numerical check cannot infer feature names or units. The request parser must enforce those separately. Numerical tests allow a difference of 0.001. Lists and structures must also have the right shape.

A three-feature batch contains legitimate zeros

This check uses the pieces from “Validate records before reducing them”.

BOTIE

Botie's service expects three finite features per row. Validate this two-row batch and return its column means. Zero and negative values are permitted by this shape-and-finiteness contract.
Input records
0-24
620
Required feature count
3

Use a number, text, or an array matching the requested result. For a matrix, put each row in brackets. Saving your prediction runs your current construction on these inputs and checks the earlier examples too.

Build a construction in the workspace above first. This case will test those pieces.

Could a valid-width batch still swap temperature and pressure columns?

A serving boundary needs semantic schema checks alongside numerical shape and finiteness checks.

This numerical check cannot infer feature names or units. The request parser must enforce those separately.

Work through the Python challenges →
Continue the courseKeeping a Prediction Consistent Across Requests →
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