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GIAC Machine Learning Engineer Sample Questions (Q138-Q143):

NEW QUESTION # 138
Which strategies can be applied to improve the anomaly detection performance of an autoencoder?
(Choose two)
Response:

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

Answer: B,C

NEW QUESTION # 139
In machine learning, what is 'data normalization'?
Response:

A. Dividing the dataset into training and test sets
B. Scaling numeric features to a standard range
C. Encoding categorical variables into numerical values
D. Removing duplicate records from the dataset

Answer: B

NEW QUESTION # 140
Which of the following are common applications of Convolutional Neural Networks?
(Choose two)
Response:

A. Time-series forecasting
B. Image classification
C. Natural language processing
D. Object detection

Answer: B,D

NEW QUESTION # 141
Your cybersecurity team is tasked with detecting anomalies in network traffic that may indicate malicious activity. You decide to use an autoencoder for this task. After training the autoencoder on normal network traffic data, you notice that it is not accurately detecting anomalies.
What are the next steps you should take to improve the performance of the autoencoder?
Response:

A. Train the autoencoder solely on anomalous data to improve its accuracy
B. Retrain the autoencoder with fewer data points and remove regularization techniques
C. Adjust the size of the latent space and apply regularization techniques to reduce overfitting
D. Increase the complexity of the network by adding more layers and disabling dropout

Answer: C

NEW QUESTION # 142
In CNNs, what is the purpose of pooling layers?
Response:

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

Answer: D

NEW QUESTION # 143
......

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