A Machine Learning Specialist Works for a Fruit Processing Company

question 57

Multiple Choice

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. The company requires at least 85% accuracy to make use of the model. After an exhaustive grid search, the optimal hyperparameters produced the following: 68% accuracy on the training set 67% accuracy on the validation set What can the machine learning specialist do to improve the system's accuracy?

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

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