ML development risks · Question 22 of 60
Which mitigations help against a defect in a library used by the framework or a defective algorithm implementation?
2 answers are correct. Medium
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Answer
- B ML functional performance testing
- D Back-to-back testing
Explanation
ML functional performance testing and back-to-back testing help against a defect in a library used by the framework, for example in PyTorch, and against a defective algorithm implementation.