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GIAC Machine Learning Engineer Sample Questions (Q75-Q80):
NEW QUESTION # 75
What does Bayes' Theorem provide in the context of machine learning?
Response:
- A. A mechanism for speeding up computations
- B. A strategy for optimizing neural networks
- C. A technique for visualizing data distributions
- D. A method for calculating the likelihood of different hypotheses
Answer: D
NEW QUESTION # 76
Unsupervised learning is primarily used for:
Response:
- A. Regression analysis with continuous output
- B. Classification tasks with predefined categories
- C. Finding hidden patterns in unlabeled data
- D. Predicting outcomes based on labeled data
Answer: C
NEW QUESTION # 77
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. Train the autoencoder solely on anomalous data to improve its accuracy
- 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. Increase the complexity of the network by adding more layers and disabling dropout
Answer: C
NEW QUESTION # 78
Which of the following are important when using standard deviation to understand data spread?
(Choose two)
Response:
- A. A large standard deviation means that data points are more spread out
- B. Standard deviation is not influenced by outliers
- C. Standard deviation can only be used for categorical data
- D. A small standard deviation means that data points are close to the mean
Answer: A,D
NEW QUESTION # 79
What is a primary goal of data visualization in machine learning?
Response:
- A. To identify patterns and insights in data
- B. To replace the need for statistical analysis
- C. To reduce the dimensionality of data
- D. To optimize the model's performance
Answer: A
NEW QUESTION # 80
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