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GIAC Machine Learning Engineer Sample Questions:

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

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

2. Which of the following are key characteristics of genetic algorithms used in neural network optimization?
(Choose two)
Response:

A) Evolution through mutation and crossover
B) Manual selection of hyperparameters
C) Fitness evaluation based on a predefined objective
D) Random initialization of weights

3. What is the primary goal of a 'confusion matrix' in classification problems?
Response:

A) To calculate the loss function of the model
B) To visualize the model's performance by showing true and false predictions
C) To display the number of features used in the model
D) To determine the optimal number of clusters

4. What is the main purpose of the matplotlib library in Python for machine learning?
Response:

A) Data visualization
B) Statistical data analysis
C) Database management
D) Deep learning model building

5. You are using a CNN to classify images in a dataset. After several epochs of training, you notice that the model performs well on the training set but poorly on the validation set. This suggests overfitting.
What steps should you take to improve the generalization of the model?
Response:

A) Implement dropout in the fully connected layers, apply data augmentation to increase the variability of the training data, and consider early stopping to prevent overfitting
B) Train the model for more epochs and reduce the use of regularization
C) Remove padding to simplify the architecture
D) Reduce the size of the dataset and increase the number of convolutional layers

Solutions: