In recent past there has been a spate of accidents involving AI and Machine learning models in practice and deployment. Much so that there is an active database of all such accidents being chronicled (https://incidentdatabase.ai/ ). At a time when AI is making strides in radical business transformation for enterprises, it is vital that we ensure …
10 Most Recommended Tests for your AI/ML/DL Models in 2022 Read More »
The current notions of quality assurance and testing in AI/ML pipelines is based on the idea of validation using a random set-aside set of data on which the model is tested and metrics computed thereof. Metrics like accuracy on the random set-aside data set termed ambiguously as test data, is the usual rubric for evaluation …
Why current testing processes in AI/ML are not enough? Read More »
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