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GIAC Machine Learning Engineer Sample Questions (Q27-Q32):

NEW QUESTION # 27
What role does 'batch size' play in training neural networks?
Response:

A. It determines the maximum number of features used in the model
B. It adjusts the learning rate of the model
C. It specifies the number of training examples used in one iteration
D. It sets the total number of training iterations

Answer: C

NEW QUESTION # 28
What is the primary goal of a 'confusion matrix' in classification problems?
Response:

A. To visualize the model's performance by showing true and false predictions
B. To calculate the loss function of the model
C. To display the number of features used in the model
D. To determine the optimal number of clusters

Answer: A

NEW QUESTION # 29
What does Bayes' Theorem provide in the context of machine learning?
Response:

A. A mechanism for speeding up computations
B. A strategy for optimizing neural networks
C. A method for calculating the likelihood of different hypotheses
D. A technique for visualizing data distributions

Answer: C

NEW QUESTION # 30
In machine learning, what does 'ensemble learning' refer to?
Response:

A. Implementing deep learning models
B. Combining multiple learning algorithms to improve performance
C. Using a single algorithm to train models
D. Reducing the dimensionality of the input data

Answer: B

NEW QUESTION # 31
In CNNs, what is the purpose of pooling layers?
Response:

A. To directly classify images
B. To increase the depth of the network
C. To reduce the spatial size of the representation
D. To increase the network's sensitivity to noise

Answer: C

NEW QUESTION # 32
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