AI0-001 Machine Learning and Deep Learning Practice Question
Which TWO are valid techniques to reduce overfitting in a deep neural network? (Choose TWO.)
⚠ Common exam trap
CompTIA often tests the distinction between techniques that improve training stability (like gradient clipping or adjusting batch size/learning rate) versus those that directly regularize the model to reduce overfitting (like L2 regularization and dropout), leading candidates to confuse optimization tricks with regularization methods.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
L2 regularization
L2 regularization (option C) is a valid technique to reduce overfitting by adding a penalty term proportional to the square of the weight magnitudes to the loss function. This discourages the network from learning overly complex patterns, effectively shrinking weights and improving generalization. Dropout (option E) randomly drops a fraction of neurons during training, which prevents co-adaptation of features and forces the network to learn more robust representations, also reducing overfitting.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase batch size
Why it's wrong here
Increasing batch size can sometimes lead to sharper minima and may not reduce overfitting.
- ✗
Increase learning rate
Why it's wrong here
Increasing learning rate can cause instability, not reduce overfitting.
- ✓
L2 regularization
Why this is correct
L2 regularization adds a penalty for large weights, discouraging complex models.
- ✗
Gradient clipping
Why it's wrong here
Gradient clipping prevents exploding gradients, not overfitting.
- ✓
Dropout
Why this is correct
Dropout randomly deactivates neurons, preventing co-adaptation and reducing overfitting.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.