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You have built a deep learning neural network that has 8 layers, and each layer has 100 fully connected nodes. The model fits the training data quite well with an F1 score of 98 out of 100. The model performs poorly when the test data is used, resulting in an F1 score of 62 out of 100. What technique would you use to try to improve performance of this model?

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You have built a deep learning neural network that has 8 layers, and each layer has 100 fully connected nodes. The model fits the training data quite well with an F1 score of 98 out of 100. The model performs poorly when the test data is used, resulting in an F1 score of 62 out of 100. What technique would you use to try to improve performance of this model?






 
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