PDE Question 77

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose B3

  B is correct

• 1

  B should be correct. Increasing the layers can also decrease the training time but may introduce vanishing gradient hence D may not be correct

• 9

  Answer: B. Subsample your training dataset. Subsampling your training dataset can help increase the training speed of your neural network model. By reducing the size of your training dataset, you can speed up the process of updating the weights in your neural network. This can help you quickly test and iterate your model to improve its accuracy. Subsampling your test dataset, on the other hand, can lead to inaccurate evaluation of your model's performance and may result in overfitting. It is important to evaluate your model's performance on a representative test dataset to ensure that it can generalize to new data. Increasing the number of input features or layers in your neural network can also improve its performance, but this may not necessarily increase the training speed. In fact, adding more layers or features can increase the complexity of your model and make it take longer to train. It is important to balance the model's complexity with its performance and training time.