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Diagnose: Ensuring Effectiveness
Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction, and skillful execution.
—John Ruskin
As we embark on this next phase, we’ll work to validate the effectiveness of the AI model. We’ll focus on ensuring a high quality of output, which requires a multifaceted approach. Exploration of the training components, rigorous testing, and ensuring responsible AI practices are all important for the quality assessment to be successful. Model validation and taking a structured approach is essential and involves validating the model’s performance against predefined criteria. Various testing methods on different model attributes can be utilized to ensure accuracy, ...
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