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GIAC GMLE Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Model Evaluation and Optimization | - Model tuning
|
| Topic 2: Data Preparation and Feature Engineering | - Data preprocessing
|
| Topic 3: Advanced Topics | - MLOps concepts
|
| Topic 4: Machine Learning Foundations | - Mathematical and statistical fundamentals
|
| Topic 5: Machine Learning Models | - Unsupervised learning
|
| Topic 6: Machine Learning Engineering and Deployment | - ML pipelines
|
GIAC Machine Learning Engineer Sample Questions:
What is the main purpose of the 'softmax' function in neural networks?
Response:
- A. To convert the output of the network into probability distributions
- B. To speed up the computation in neural networks
- C. To normalize the input data
- D. To introduce non-linearity into the network
What does 'one-hot encoding' do in the preprocessing of categorical data?
Response:
- A. It converts categorical variables into binary vectors
- B. It identifies and removes outliers
- C. It scales all features to a uniform range
- D. It reduces the dimensionality of the data
Which of the following are characteristics of hierarchical clustering?
(Choose two)
Response:
- A. It can be either agglomerative or divisive
- B. It requires specifying the number of clusters in advance
- C. It creates a tree-like structure of nested clusters
- D. It scales better for large datasets compared to k-means
Overfitting in supervised learning models refers to:
Response:
- A. The process of training models on large datasets
- B. Models performing equally on training and test data
- C. Models capturing noise in the training data as if it were a true signal
- D. Models that are too simplistic to capture underlying patterns
Which techniques can help prevent overfitting in Convolutional Neural Networks?
(Choose two)
Response:
- A. Increasing the number of convolutional layers
- B. Dropout
- C. Early stopping
- D. Max pooling
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