You are an engineer that developed an AI-based ad recommendation tool.
Which of the following should be monitored to evaluate the tool ' s effectiveness?
Which of the following considerations is the most important in mitigating the potential of bias in training and testing data?
What is the best method to proactively train an LLM so that there is mathematical proof that no specific piece of training data has more than a negligible effect on the model or its output?
What is the technique to remove the effects of improperly used data from an ML system?
