LATEST GMLE TEST FORMAT, GMLE PASSED

Latest GMLE Test Format, GMLE Passed

Latest GMLE Test Format, GMLE Passed

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Tags: Latest GMLE Test Format, GMLE Passed, GMLE Test Fee, Exam GMLE Labs, GMLE Valid Test Prep

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GIAC Machine Learning Engineer Sample Questions (Q34-Q39):

NEW QUESTION # 34
Which are common sources of data used in machine learning pipelines?
(Choose two)
Response:

  • A. Web scraping
  • B. Model ensembling
  • C. APIs
  • D. Manual calculations

Answer: A,C


NEW QUESTION # 35
Which techniques are commonly used to optimize neural networks during training?
(Choose two)
Response:

  • A. Data augmentation
  • B. Stochastic Gradient Descent
  • C. Softmax activation function
  • D. Adam optimizer

Answer: B,D


NEW QUESTION # 36
You are tasked with collecting data from an external API for use in a machine learning model. After making several requests, you notice that the data contains missing values and inconsistencies across different records. What steps should you take to clean and prepare this data for further analysis and modeling?
Response:

  • A. Collect additional data from a different source without fixing the original dataset
  • B. Focus on fixing inconsistencies only in the training data, ignoring the test data
  • C. Identify and remove records with missing values, apply data normalization techniques, and ensure data consistency before model training
  • D. Ignore the inconsistencies and proceed directly to model training

Answer: C


NEW QUESTION # 37
What are heatmaps used for in data visualization?
Response:

  • A. Plotting data over time
  • B. Showing the relationship between two variables
  • C. Representing the magnitude of phenomena as color in two dimensions
  • D. Displaying geographical data

Answer: C


NEW QUESTION # 38
How does 'L1 regularization' differ from 'L2 regularization' in machine learning?
Response:

  • A. L1 is used for regression; L2 is used for classification
  • B. L1 is for neural networks; L2 is for decision trees
  • C. L1 adds the absolute value of coefficients; L2 adds the square of coefficients
  • D. L1 optimizes the learning rate; L2 optimizes the batch size

Answer: C


NEW QUESTION # 39
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