Exam AWS Certified Machine Learning - Specialty topic 1 question 95 discussion

Answer A.

The answer is Early Stopping. Stopp the training before accuracy start do decrease.

I will go with A Early stopping is a powerful technique to prevent overfitting. It involves monitoring the model’s performance on a validation dataset during training. If the validation loss starts increasing or plateaus, early stopping stops further training. This ensures that the model doesn’t overfit to the training data. Based on the graph, if the validation loss begins to stagnate or increase after a certain number of epochs, enabling early stopping could lead to better generalization.

early stopping before error increase

Early stopping

Early stopping

A: stop the training process of a neural network before it reaches the maximum number of epochs or iterations; in this case stop close to 64 Epochs.

Early stopping and not increasing epochs.

Answer is ”A”

Early Stopping can improve the model?

A is the answer

I would go for A

I would choose A.