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GIAC Machine Learning Engineer Sample Questions:

1. Which of the following are common activation functions used in neural networks?
(Choose two)
Response:

A) ReLU (Rectified Linear Unit)
B) Weight initialization
C) Sigmoid function
D) Batch normalization

2. Why is feature scaling important in machine learning?
Response:

A) It makes the model training process faster
B) It increases the number of features
C) It helps in handling missing data
D) It ensures that different features contribute equally to the model training

3. Which of the following are common applications of Bayes' Theorem in machine learning?
(Choose two)
Response:

A) Creating Naive Bayes classifiers
B) Building decision trees
C) Developing recommendation systems
D) Calculating the posterior probability in classification tasks

4. Which of the following is a key advantage of Convolutional Neural Networks (CNNs) in image classification?
Response:

A) They perform well with structured data
B) They are easy to interpret
C) They reduce the need for feature engineering by learning features automatically from images
D) They work best with time-series data

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

Solutions: