How do I evaluate AI models effectively?

How do I evaluate AI models effectively?

To evaluate AI models, you can use metrics like accuracy, precision, recall, and F1 score. What type of model are you working with?

I'm working with a classification model for image recognition.

For image recognition, you might also consider using confusion matrices and ROC curves. Have you already split your data into training and testing sets?

Yes, I have a training set and a validation set. What should I do next?

Next, you can train your model on the training set and then evaluate its performance on the validation set using the metrics we discussed.

What if the model performs poorly on the validation set?

If the model performs poorly, you might need to tune hyperparameters, try different algorithms, or augment your training data.