Microsoft DP-100 Designing and Implementing a Data Science Solution on Azure 04 31Oct2024 - Practice Quiz

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A computer vision team is developing a Convolutional Neural Network (CNN) to classify images of animals. They decide to implement a CNN architecture that includes multiple convolutional layers followed by pooling layers. After training the model, they notice that the accuracy on the training set is significantly higher than on the validation set. To address this issue, they consider various strategies to improve the model\'s generalization. Which of the following strategies would most effectively reduce overfitting in this scenario?

Implementing dropout layers in the network architecture

Increasing the number of convolutional filters in each layer

Using a larger batch size during training

Adding more convolutional layers to the network

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