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GIAC Machine Learning Engineer Sample Questions:

1. 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) Increase the complexity of the network by adding more layers and disabling dropout
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) Train the autoencoder solely on anomalous data to improve its accuracy

2. Which of the following best describes linear regression?
Response:

A) A clustering algorithm
B) A neural network technique
C) A technique for predicting a continuous target variable based on input features
D) A method for classifying data into categories

3. Which of the following are common applications of Convolutional Neural Networks?
(Choose two)
Response:

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

4. In deep learning, 'dropout' is a technique used to:
Response:

A) Reduce data dimensionality
B) Prevent overfitting
C) Speed up computations
D) Increase model accuracy

5. What does 'data imputation' refer to in data preprocessing?
Response:

A) Scaling data to a standard range
B) Removing irrelevant features from the dataset
C) Filling in missing or null values in the data
D) Transforming categorical data into numerical data

Solutions: