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GIAC GMLE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Python for Machine Learning | 15% | - Data science libraries (Pandas, NumPy, Matplotlib) - Scripting and automation for security data - Machine learning frameworks (Scikit-learn, TensorFlow, PyTorch) |
| Supervised Machine Learning | 15% | - Model training, validation and evaluation - Feature engineering and selection - Classification and regression algorithms |
| Unsupervised Machine Learning | 12% | - Clustering and dimensionality reduction - Pattern recognition in security data - Anomaly detection techniques |
| Deep Learning and Neural Networks | 13% | - Autoencoders and generative models - Neural network fundamentals - Convolutional Neural Networks (CNN) |
| Machine Learning for Cybersecurity | 15% | - Threat hunting and behavioral analytics - Security monitoring and anomaly detection - Malware analysis and classification |
| Data Acquisition, Preparation and Exploration | 15% | - Data cleaning, transformation and normalization - Exploratory data analysis and visualization - Data collection methods (SQL, web scraping, APIs) |
| Statistics and Probability for Data Science | 15% | - Statistical testing and hypothesis testing - Probability theory and distributions - Descriptive and inferential statistics |
GIAC Machine Learning Engineer Sample Questions:
In machine learning, what does 'pruning' a decision tree involve?
Response:
- A. Removing branches to reduce complexity and overfitting
- B. Adding more branches to the tree
- C. Splitting the tree into multiple smaller trees
- D. Increasing the depth of the tree
Correct Answer: A π³οΈ
Which of the following best describes standard deviation?
Response:
- A. It represents the most frequent value in a dataset
- B. It is the difference between the largest and smallest values
- C. It measures the spread of data points from the mean
- D. It is the average of all the values in the dataset
Correct Answer: C π³οΈ
What does the term 'reinforcement learning' refer to in machine learning?
Response:
- A. The method of combining multiple models to improve performance
- B. A type of unsupervised learning
- C. A learning technique where an agent learns to make decisions by taking actions in an environment to achieve some reward
- D. The process of training neural networks with backpropagation
Correct Answer: C π³οΈ
Which techniques can help prevent overfitting in Convolutional Neural Networks?
(Choose two)
Response:
- A. Dropout
- B. Early stopping
- C. Increasing the number of convolutional layers
- D. Max pooling
Correct Answer: A,B π³οΈ
P-values in hypothesis testing are used to:
Response:
- A. Determine the practical significance of results
- B. Estimate the probability of observing the data given the null hypothesis is true
- C. Calculate the mean of the data sample
- D. Visualize the distribution of data
Correct Answer: B π³οΈ
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