A team is training a deep neural network for fraud detection. The training accuracy is 99.5%, but the validation accuracy is only 91%. The model has three hidden layers with 512 neurons each. Which change is most likely to improve validation performance?

Add dropout layers with a rate of 0.5 after each hidden layer.

Increase the number of training epochs to allow better convergence.

Remove the activation functions from the hidden layers.

Increase the number of neurons in each hidden layer to 1024.

In batch normalization, what is normalized for each feature across a mini-batch?

The gradients of the loss function

The mean and variance of the activations

The learning rate for each parameter

Which of the following best describes the structure of a typical feedforward artificial neural network?

A single layer of neurons that directly maps inputs to outputs without any hidden layers

A cyclic graph where outputs feed back into inputs, allowing temporal processing

An input layer, one or more hidden layers, and an output layer, where data flows in one direction

A structure where each neuron is connected to every other neuron in the network, including itself

CompTIADataX

Domain 3Objective 4

Deep Learning DY0-001 Practice Questions (Page 3)

Part of the Machine learning domain, which accounts for 24% of the DY0-001 exam. CompTIA does not publish an official question count, but from its 165-minute exam (~65–110 total, ~16–26 in this domain), expect 3–5 from this objective — we provide 24 practice questions to prepare you well beyond it. (estimate)

24questions here

5free pages

5concepts

24%of the exam

Questions 11–15

11foundation · easy
Which deep-learning framework is known for its high-level API that can run on top of TensorFlow, making it easy to build and train neural networks with minimal code?
Select an answer first
12application · medium
A team is training a deep neural network for fraud detection. The training accuracy is 99.5%, but the validation accuracy is only 91%. The model has three hidden layers with 512 neurons each. Which change is most likely to improve validation performance?
Select an answer first
13foundation · easy
In batch normalization, what is normalized for each feature across a mini-batch?
Select an answer first
14foundation · easy
Which deep-learning framework is known for its dynamic computation graph, which allows for flexible model building and debugging, making it popular in research?
Select an answer first
15foundation · easy
Which of the following best describes the structure of a typical feedforward artificial neural network?
Select an answer first

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Deep Learning DY0-001 Practice Questions (Page 3)

Questions 11–15

Which deep-learning framework is known for its high-level API that can run on top of TensorFlow, making it easy to build and train neural networks with minimal code?

A team is training a deep neural network for fraud detection. The training accuracy is 99.5%, but the validation accuracy is only 91%. The model has three hidden layers with 512 neurons each. Which change is most likely to improve validation performance?

In batch normalization, what is normalized for each feature across a mini-batch?

Which deep-learning framework is known for its dynamic computation graph, which allows for flexible model building and debugging, making it popular in research?

Which of the following best describes the structure of a typical feedforward artificial neural network?

Keep studying — Machine learning