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GIAC Machine Learning Engineer Sample Questions (Q123-Q128):

NEW QUESTION # 123
Which of the following best describes standard deviation?
Response:

A. It is the difference between the largest and smallest values
B. It represents the most frequent value in a dataset
C. It is the average of all the values in the dataset
D. It measures the spread of data points from the mean

Answer: D

NEW QUESTION # 124
What role does 'batch size' play in training neural networks?
Response:

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

Answer: C

NEW QUESTION # 125
Which strategies can be applied to improve the anomaly detection performance of an autoencoder?
(Choose two)
Response:

A. Increase the size of the latent space
B. Train the autoencoder on both normal and anomalous data
C. Add regularization techniques such as L1 or L2
D. Reduce the number of hidden layers

Answer: B,C

NEW QUESTION # 126
You are analyzing the performance of machine learning models by comparing their error rates. After calculating the mean and standard deviation of the errors for each model, you notice that one model has a high standard deviation compared to the others.
What does this suggest about the model's performance, and what steps can you take to improve it?
Response:

A. The model's performance is optimal, and no changes are needed
B. The mean error is sufficient to evaluate performance, and standard deviation can be ignored
C. The high standard deviation suggests that the model's errors are inconsistent; you should apply regularization or tune hyperparameters to reduce variability
D. Increase the dataset size without making any changes to the model

Answer: C

NEW QUESTION # 127
In the context of random forests, what is bagging?
Response:

A. A method used to select the best hyperparameters for a model
B. A process that reduces the dimensionality of the dataset
C. A technique that reduces overfitting by using a combination of decision trees trained on different subsets of the data
D. A clustering algorithm that groups similar data points

Answer: C

NEW QUESTION # 128
......

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GMLE Exam Preparatory: GIAC Machine Learning Engineer & GMLE Test Questions

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Printable GMLE PDF, GIAC Dumps GMLE PDF: GIAC Machine Learning Engineer Pass Certainly

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GIAC Machine Learning Engineer Sample Questions (Q123-Q128):

GMLE Exam Preparatory: GIAC Machine Learning Engineer & GMLE Test Questions

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