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GIAC Machine Learning Engineer Sample Questions:

1. What does 'one-hot encoding' do in the preprocessing of categorical data?
Response:

A) It scales all features to a uniform range
B) It reduces the dimensionality of the data
C) It converts categorical variables into binary vectors
D) It identifies and removes outliers

2. What is Random Forest an example of?
Response:

A) A neural network architecture
B) An ensemble learning method
C) A clustering algorithm
D) A reinforcement learning technique

3. In the context of anomaly detection, which is the primary advantage of using autoencoders?
Response:

A) They are capable of detecting complex, non-linear anomalies
B) They reduce the dimensionality of the input data
C) They are faster to train than traditional algorithms
D) They can handle both structured and unstructured data

4. Which techniques can help prevent overfitting in Convolutional Neural Networks?
(Choose two)
Response:

A) Increasing the number of convolutional layers
B) Early stopping
C) Dropout
D) Max pooling

5. You are tasked with clustering a large dataset of customer transactions to identify patterns of behavior. You have chosen k-means clustering but are unsure of the optimal number of clusters to use. What steps should you take to determine the optimal number of clusters and ensure high-quality clustering?
Response:

A) Use hierarchical clustering to identify clusters and apply the same number to k-means
B) Randomly select the number of clusters and observe the clustering performance
C) Use the elbow method to plot the within-cluster sum of squares and determine the point where the improvement diminishes, and use the silhouette score to evaluate cluster cohesion
D) Start with a large number of clusters and manually reduce them over time

Solutions: