Exam Professional Data Engineer topic 1 question 77 discussion

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.

B is correct

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

answer is B

Reduce training time and probably accuracy too.

all other are wrong

of course !

B. Subsampling your training dataset can decrease the amount of data the model needs to process and can speed up training time. However, it can lead to decrease in the model's accuracy. Although it shouldn't matter since we are not even in testing phase yet and we aren't looking for accuracy.

B is the answer as we are bothered about speed not the accuracy.

The answer is B. Building a more complex model by increasing the number of layer will not reduce the training time.

By SubSampling the training data, you will reduce the training time. In case of D, if you increase the number of layers, then the model's accuracy will be increased. But it will not reduce the time required to train the model.

Increase speed of the help to train quicker.. option B is sub sample that also help but it drop accurately of model . So I think Option D is good to go.

B is the answer.

It is B. D would improve the accuracy, not speed.

It's B. D Would be for increase performance

if you Increase the number of layers, you increase the training time, right?

Both B and D seems correct.