How do I evaluate my TensorFlow model?

How do I evaluate my TensorFlow model?

To evaluate your TensorFlow model, you can use the model.evaluate() method, which computes the loss and any additional metrics you specified during compilation.

What metrics should I use for evaluation?

Common metrics include accuracy, precision, recall, and F1 score. The choice depends on your specific problem.

Can I visualize the evaluation results?

Yes, you can use libraries like Matplotlib or Seaborn to create visualizations of your evaluation metrics.

How do I handle overfitting during evaluation?

To handle overfitting, you can use techniques like cross-validation, regularization, or dropout during training.