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GIAC Machine Learning Engineer Sample Questions:

1. In machine learning, what is 'dimensionality reduction' used for?
Response:

A) To increase the computational speed of model training
B) To reduce the number of input variables, simplifying the model
C) To improve the model's accuracy on training data
D) To enhance the feature importance analysis

2. Which of the following statements about frequency distribution is correct?
Response:

A) It displays how frequently different values occur in a dataset
B) It measures the median of the dataset
C) It provides a method to reduce dimensionality
D) It predicts future data points based on historical data

3. In machine learning, what does 'model generalization' mean?
Response:

A) The model's ability to perform well on new, unseen data
B) Combining multiple models to improve performance
C) Increasing the number of features in the model
D) Simplifying the model to make it more interpretable

4. Which Python function from the Pandas library is used to load data from a CSV file?
Response:

A) np.load()
B) tf.load_model()
C) plt.load()
D) pd.read_csv()

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 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
B) Start with a large number of clusters and manually reduce them over time
C) Use hierarchical clustering to identify clusters and apply the same number to k-means
D) Randomly select the number of clusters and observe the clustering performance

Solutions: