Remove Data-driven Remove Experimentation Remove Key Performance Indicator Remove Uncertainty
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. It helps you to amplify what’s proven to work, throw away what isn’t, and tweak the goal-posts when data indicates that they may be in the wrong place.

Metrics 156
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AI Product Management After Deployment

O'Reilly on Data

From a technical perspective, it is entirely possible for ML systems to function on wildly different data. For example, you can ask an ML model to make an inference on data taken from a distribution very different from what it was trained on—but that, of course, results in unpredictable and often undesired performance.