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GIAC Machine Learning Engineer Sample Questions (Q36-Q41):
NEW QUESTION # 36
Stochastic Gradient Descent differs from traditional Gradient Descent by:
Response:
- A. Using a fixed learning rate throughout the training process
- B. Updating model parameters after evaluating each data point
- C. Updating model parameters after evaluating the entire dataset
- D. Eliminating the need for a learning rate
Answer: B
ย
NEW QUESTION # 37
Which techniques are commonly used to optimize neural networks during training?
(Choose two)
Response:
- A. Softmax activation function
- B. Data augmentation
- C. Stochastic Gradient Descent
- D. Adam optimizer
Answer: C,D
ย
NEW QUESTION # 38
In machine learning, what does 'ensemble learning' refer to?
Response:
- A. Reducing the dimensionality of the input data
- B. Implementing deep learning models
- C. Combining multiple learning algorithms to improve performance
- D. Using a single algorithm to train models
Answer: C
ย
NEW QUESTION # 39
What is NumPy essential for in data science?
Response:
- A. Handling large arrays and matrices efficiently
- B. Text processing and natural language understanding
- C. Web scraping and data collection
- D. Building interactive dashboards
Answer: A
ย
NEW QUESTION # 40
The term 'convolution' in CNNs refers to:
Response:
- A. The process of combining multiple neural networks
- B. A function applied to reduce the size of the data
- C. A specialized neural network layer for image processing
- D. A technique for accelerating network training
Answer: C
ย
NEW QUESTION # 41
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