AWS Certified Machine Learning – Specialty — Question 164

A manufacturing company asks its machine learning specialist to develop a model that classifies defective parts into one of eight defect types. The company has provided roughly 100,000 images per defect type for training. During the initial training of the image classification model, the specialist notices that the validation accuracy is 80%, while the training accuracy is 90%. It is known that human-level performance for this type of image classification is around 90%.
What should the specialist consider to fix this issue?

Answer options

• A. A longer training time
• B. Making the network larger
• C. Using a different optimizer
• D. Using some form of regularization

Correct answer: D

Explanation

The correct answer is D, as using regularization techniques can help reduce overfitting, which is indicated by the higher training accuracy compared to validation accuracy. The other options may not effectively address the overfitting issue; simply increasing training time or network size could worsen it, and changing optimizers may not solve the underlying problem.