Why is initial validation important in AI models?

Why is initial validation important in AI models?

Initial validation is crucial as it ensures the model's accuracy and reliability before deployment.

What are the risks of skipping initial validation?

Skipping initial validation can lead to poor performance, biased results, and potential harm in real-world applications.

How can I perform initial validation effectively?

You can perform initial validation by using a representative dataset, cross-validation techniques, and evaluating key performance metrics.

What metrics should I focus on during initial validation?

Focus on metrics like accuracy, precision, recall, and F1 score to assess your model's performance.

Can initial validation help in model improvement?

Yes, initial validation provides insights that can guide adjustments and enhancements to improve the model's performance.