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GIAC Machine Learning Engineer Sample Questions (Q83-Q88):

NEW QUESTION # 83
What role does 'dropout' play in training deep neural networks?
Response:

A. It introduces non-linearity into the model
B. It accelerates the training process
C. It increases the accuracy of the model on the training data
D. It helps prevent overfitting by randomly dropping units during training

Answer: D

NEW QUESTION # 84
Which of the following are common applications of regression models?
(Choose two)
Response:

A. Clustering customer segments
B. Predicting house prices based on various features
C. Forecasting sales trends over time
D. Classifying spam emails

Answer: B,C

NEW QUESTION # 85
Which of the following are common supervised learning algorithms?
(Choose two)
Response:

A. k-means
B. Linear Regression
C. DBSCAN
D. Random Forest

Answer: B,D

NEW QUESTION # 86
What is 'feature importance' in the context of machine learning models?
Response:

A. The step of removing irrelevant features from the model
B. The technique of encoding categorical features
C. The measure of a feature's contribution to the model's prediction
D. The process of adding new features to the model

Answer: C

NEW QUESTION # 87
How does 'L1 regularization' differ from 'L2 regularization' in machine learning?
Response:

A. L1 optimizes the learning rate; L2 optimizes the batch size
B. L1 is for neural networks; L2 is for decision trees
C. L1 adds the absolute value of coefficients; L2 adds the square of coefficients
D. L1 is used for regression; L2 is used for classification

Answer: C

NEW QUESTION # 88
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