{"id":497,"date":"2023-01-14T11:09:00","date_gmt":"2023-01-14T11:09:00","guid":{"rendered":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/aws-certified-machine-learning-specialty-mls-c01-question098\/"},"modified":"2023-01-14T11:09:00","modified_gmt":"2023-01-14T11:09:00","slug":"aws-certified-machine-learning-specialty-mls-c01-question098","status":"publish","type":"post","link":"https:\/\/exampracticetests.com\/aws\/Machine_Learning-Specialty_MLS-C01\/aws-certified-machine-learning-specialty-mls-c01-question098\/","title":{"rendered":"AWS Certified Machine Learning – Specialty MLS-C01 – Question098"},"content":{"rendered":"
A machine learning specialist works for a fruit processing company and needs to build a system that categorizes apples into three types. The specialist has collected a dataset that contains 150 images for each type of apple and applied transfer learning on a neural network that was pretrained on ImageNet with this dataset.
\nThe company requires at least 85% accuracy to make use of the model.
\nAfter an exhaustive grid search, the optimal hyperparameters produced the following:
\n– 68% accuracy on the training set
\n– 67% accuracy on the validation set
\nWhat can the machine learning specialist do to improve the system's accuracy?

A.<\/strong> Upload the model to an Amazon SageMaker notebook instance and use the Amazon SageMaker HPO feature to optimize the model's hyperparameters.
B.<\/strong> Add more data to the training set and retrain the model using transfer learning to reduce the bias.
C.<\/strong> Use a neural network model with more layers that are pretrained on ImageNet and apply transfer learning to increase the variance.
D.<\/strong> Train a new model using the current neural network architecture.<\/div>\n

<\/p>\n