lesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriouslylesson 7 of 7 · the ml-system option — six boring stages that get a repo taken seriouslythe ml-system option — six boring stages that get a repo taken seriously
A pipeline run just finished. Training accuracy is a glowing 0.98. Held-out accuracy is 0.78. The bar is 0.80.
Predict all three output lines — the row count after
validation, the accuracy line, and the gate's verdict. One of
the four numbers in run never gets read at all. Which one?