How do I evaluate the quality of my training data for AI models?

How do I evaluate the quality of my training data for AI models?

Evaluating training data quality involves checking for accuracy, relevance, and diversity. What specific aspects are you concerned about?

I'm worried about the accuracy and bias in my dataset.

To assess accuracy, you can compare your data against trusted sources. For bias, consider analyzing the distribution of different categories in your data.

What tools can I use to analyze bias in my dataset?

You can use tools like Fairness Indicators, AI Fairness 360, or What-If Tool to analyze and visualize bias in your dataset.

Can you give me an example of how to use one of those tools?

Sure! For instance, with AI Fairness 360, you can load your dataset, apply bias detection metrics, and visualize the results to identify any disparities.