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GIAC Machine Learning Engineer Sample Questions:

1. What is the purpose of inferential statistics in machine learning?
Response:

A) To make predictions about a population based on a sample
B) To visualize complex datasets
C) To describe the basic features of data
D) To classify data into different categories

2. 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) Retrain the autoencoder with fewer data points and remove regularization techniques
B) Train the autoencoder solely on anomalous data to improve its accuracy
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

3. Which of the following metrics is commonly used to evaluate the performance of a regression model?
Response:

A) Confusion matrix
B) Mean Squared Error (MSE)
C) F1 score
D) Precision

4. Which loss function is typically used for regression problems?
Response:

A) Kullback-Leibler divergence
B) Cross-entropy loss
C) Mean Squared Error (MSE)
D) Hinge loss

5. Which of the following are common supervised learning algorithms?
(Choose two)
Response:

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

Solutions: