This graph shows the training and validation loss against the epochs for a neural network. The network being trained is as follows: ✑ Two dense layers, one output neuron ✑ 100 neurons in each layer ✑ 100 epochs Random initialization of weights Which technique can be used to improve model performance in terms of accuracy in the validation set?

Questions › Category: MLS-C01 › This graph shows the training and validation loss against the epochs for a neural network. The network being trained is as follows: ✑ Two dense layers, one output neuron ✑ 100 neurons in each layer ✑ 100 epochs Random initialization of weights Which technique can be used to improve model performance in terms of accuracy in the validation set?

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Admin Staff asked 3 months ago

This graph shows the training and validation loss against the epochs for a neural network.
The network being trained is as follows:
✑ Two dense layers, one output neuron
✑ 100 neurons in each layer
✑ 100 epochs
Random initialization of weights
 
 
Which technique can be used to improve model performance in terms of accuracy in the validation set?

A. Early stopping

B. Random initialization of weights with appropriate seed

C. Increasing the number of epochs

D. Adding another layer with the 100 neurons








 

Suggested Answer: C

Community Answer: A




This question is in MLS-C01 AWS Certified Machine Learning – Specialty Exam
For getting AWS Certified Machine Learning – Specialty Certificate


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