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GIAC Machine Learning Engineer Sample Questions:

1. You are tasked with building a classification model to predict whether customers will purchase a product based on their browsing behavior. You decide to use a Random Forest classifier. After training the model, you notice that the training accuracy is very high, but the validation accuracy is much lower.
What might be causing this, and how can you improve the model's generalization?
Response:

A) The training data is too large; reducing the training set size will improve the model's performance
B) The features are not useful; removing all but one feature will reduce overfitting
C) The model is likely overfitting to the training data; applying cross-validation and reducing the number of trees in the forest or using regularization techniques can help improve the generalization to unseen data
D) The model is underfitting the data; increasing the number of features and trees will improve performance

2. What is not a typical use case for CNNs in image processing?
Response:

A) Facial recognition
B) Natural language processing
C) Image classification
D) Object detection

3. Which functions are typically used for data manipulation in the Pandas library?
(Choose two)
Response:

A) plt.show()
B) pd.DataFrame()
C) pd.merge()
D) tf.keras.models()

4. Which two types of probabilities are essential in machine learning applications?
(Choose two)
Response:

A) Absolute probability
B) Marginal probability
C) Conditional probability
D) Uncertainty probability

5. Which component of a CNN is responsible for learning the spatial hierarchies of features in an image?
Response:

A) Activation function
B) Fully connected layer
C) Convolutional layer
D) Dropout layer

Solutions: