100% PASS HIGH-QUALITY GMLE - VALID GIAC MACHINE LEARNING ENGINEER DUMPS

100% Pass High-quality GMLE - Valid GIAC Machine Learning Engineer Dumps

100% Pass High-quality GMLE - Valid GIAC Machine Learning Engineer Dumps

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GIAC Machine Learning Engineer Sample Questions (Q101-Q106):

NEW QUESTION # 101
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 neural network technique
  • D. A method for classifying data into categories

Answer: B


NEW QUESTION # 102
You are analyzing the performance of machine learning models by comparing their error rates. After calculating the mean and standard deviation of the errors for each model, you notice that one model has a high standard deviation compared to the others.
What does this suggest about the model's performance, and what steps can you take to improve it?
Response:

  • A. Increase the dataset size without making any changes to the model
  • B. The model's performance is optimal, and no changes are needed
  • C. The mean error is sufficient to evaluate performance, and standard deviation can be ignored
  • D. The high standard deviation suggests that the model's errors are inconsistent; you should apply regularization or tune hyperparameters to reduce variability

Answer: D


NEW QUESTION # 103
What is a key step in preprocessing data for machine learning?
Response:

  • A. Increasing the size of the dataset artificially
  • B. Selecting a suitable machine learning algorithm
  • C. Normalizing or standardizing the data
  • D. Simplifying the model architecture

Answer: C


NEW QUESTION # 104
SQL is commonly used in data manipulation for:
Response:

  • A. Extracting and querying data from databases
  • B. Visualizing data distributions
  • C. Implementing machine learning algorithms
  • D. Generating complex neural network models

Answer: A


NEW QUESTION # 105
What role does 'batch size' play in training neural networks?
Response:

  • A. It adjusts the learning rate of the model
  • B. It specifies the number of training examples used in one iteration
  • C. It sets the total number of training iterations
  • D. It determines the maximum number of features used in the model

Answer: B


NEW QUESTION # 106
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