Many organisations today struggle to derive business value from artificial intelligence (AI) due to the prevalence of unreliable data sets. Low-quality data is among the most significant barriers to widespread AI adoption, particularly in an enterprise setting. This is where human-in-the-loop (HITL) services become indispensable in the data preparation process.AI models, particularly complex ones like neural networks, are often seen as 'black boxes' because their decision-making processes are not easily interpretable by humans. Across the model life cycle, from model training to model fine-tuning, HITL could ensure that the data is properly........

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