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GIAC GMLE Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Model Evaluation and Optimization | - Model tuning
|
| Topic 2: Machine Learning Models | - Supervised learning models
|
| Topic 3: Data Preparation and Feature Engineering | - Feature engineering
|
| Topic 4: Machine Learning Engineering and Deployment | - ML pipelines
|
| Topic 5: Advanced Topics | - MLOps concepts
|
| Topic 6: Machine Learning Foundations | - Core ML concepts
|
GIAC Machine Learning Engineer Sample Questions:
Unsupervised learning is primarily used for:
Response:
- A. Predicting outcomes based on labeled data
- B. Classification tasks with predefined categories
- C. Finding hidden patterns in unlabeled data
- D. Regression analysis with continuous output
Correct Answer: C 🗳️
Which of the following statements about frequency distribution is correct?
Response:
- A. It measures the median of the dataset
- B. It predicts future data points based on historical data
- C. It displays how frequently different values occur in a dataset
- D. It provides a method to reduce dimensionality
Correct Answer: C 🗳️
Which of the following functions is used to calculate loss in a neural network during training?
Response:
- A. Activation function
- B. Softmax function
- C. Loss function
- D. Dropout function
Correct Answer: C 🗳️
Which of the following are common applications of regression models?
(Choose two)
Response:
- A. Predicting house prices based on various features
- B. Clustering customer segments
- C. Classifying spam emails
- D. Forecasting sales trends over time
Correct Answer: A,D 🗳️
What is the main challenge in determining the optimal number of clusters for a k-means algorithm?
Response:
- A. It depends on the amount of training data
- B. It increases the computational complexity
- C. It requires a predefined number of clusters, which may not reflect the true structure of the data
- D. It needs feature scaling before clustering
Correct Answer: C 🗳️
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