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GIAC GMLE Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Acquisition and Exploration | - Data acquisition
|
| Anomaly Detection and Optimization | - Security-focused ML applications
|
| Python for Machine Learning | - Python scripting
|
| Statistics and Probability | - Inferential statistics
|
| Machine Learning Fundamentals | - Supervised and unsupervised learning
|
| Neural Networks and Deep Learning | - Deep learning concepts
|
GIAC Machine Learning Engineer Sample Questions:
In deep learning, 'dropout' is a technique used to:
Response:
- A. Speed up computations
- B. Increase model accuracy
- C. Prevent overfitting
- D. Reduce data dimensionality
Correct Answer: C 🗳️
Which Python function from the Pandas library is used to load data from a CSV file?
Response:
- A. pd.read_csv()
- B. np.load()
- C. tf.load_model()
- D. plt.load()
Correct Answer: A 🗳️
In the context of deep learning, what is a 'convolutional layer' primarily used for?
Response:
- A. To accelerate the training process of the network
- B. To extract features from input data like images
- C. To reduce the size of the neural network
- D. To classify input data into different categories
Correct Answer: B 🗳️
You are using a CNN to classify images in a dataset. After several epochs of training, you notice that the model performs well on the training set but poorly on the validation set. This suggests overfitting.
What steps should you take to improve the generalization of the model?
Response:
- A. Train the model for more epochs and reduce the use of regularization
- B. Remove padding to simplify the architecture
- C. Implement dropout in the fully connected layers, apply data augmentation to increase the variability of the training data, and consider early stopping to prevent overfitting
- D. Reduce the size of the dataset and increase the number of convolutional layers
Correct Answer: C 🗳️
Which strategies can be applied to improve the anomaly detection performance of an autoencoder?
(Choose two)
Response:
- A. Reduce the number of hidden layers
- B. Increase the size of the latent space
- C. Train the autoencoder on both normal and anomalous data
- D. Add regularization techniques such as L1 or L2
Correct Answer: C,D 🗳️
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