What is the importance of validation in AI models?

What is the importance of validation in AI models?

Validation is crucial as it ensures that the AI model performs well on unseen data, preventing overfitting.

How does validation help in improving model accuracy?

Validation helps identify the model's weaknesses and allows for adjustments, leading to improved accuracy.

What are some common validation techniques used in AI?

Common techniques include k-fold cross-validation, holdout validation, and stratified sampling.

Can you explain overfitting and how validation prevents it?

Overfitting occurs when a model learns noise instead of the signal. Validation helps by testing the model on separate data.

What happens if I skip the validation process?

Skipping validation can lead to poor model performance in real-world applications, as it may not generalize well.