Edge AI Journey

Next best action

Run error analysis on the validation set

Training and evaluation exist. The error-analysis evidence gate is still open. Classify failures before changing the model.

LearnReady

BuildReady

MeasureNow

ProveGate

Today's plan

1 of 3 actions complete

Evidence first

Classify the top 20 validation failuresGroup failures by data, representation, optimization, and evaluation causes.45mAdd baseline metrics to the reportRecord quality, inference latency, memory, and dataset version.30mDraft the limitations sectionDocument known blind spots and conditions where the model should not be used.25m

Current gate

Error analysis report

The report must connect observed failures to a prioritized corrective experiment.

BaselineEvaluationAnalysisEvidence

Open project workspace

P-01

Active project

Vision Quality Baseline

Build a reproducible image-classification baseline with trustworthy evaluation and deployment-ready evidence.

MilestoneEvaluationEvidence3 / 6RiskDataset shift

Two-phase trajectory

Production AI EngineerApplied deep learning · active

24%

Edge AI · NVIDIAUnlock after Phase 1 gates

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Field note

Make the next hour count.

Run error analysis on the validation set

1 of 3 actions complete

Error analysis report

Vision Quality Baseline

What did the failures teach you?