- A
Linear Regression
Why wrong: Linear regression is a model, not an activation function.
- B
Support Vector Machine
Why wrong: SVM is a machine learning algorithm, not an activation function.
- C
K-means
Why wrong: K-means is a clustering algorithm.
- D
ReLU
ReLU is the most common activation for hidden layers.
- E
Sigmoid
Sigmoid is a classic activation function for output layers.
Question 535 of 1,000
AI0-001 Machine Learning and Deep Learning Practice Question
This AI0-001 practice question tests your understanding of machine learning and deep learning. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which TWO of the following are common activation functions used in deep neural networks?
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
✓
ReLU
ReLU (Rectified Linear Unit) is a common activation function in deep neural networks because it introduces non-linearity while being computationally efficient, outputting the input directly if positive and zero otherwise. It helps mitigate the vanishing gradient problem, making it a default choice for hidden layers in many architectures.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Linear Regression
Why it's wrong here
Linear regression is a model, not an activation function.
- ✗
Support Vector Machine
Why it's wrong here
SVM is a machine learning algorithm, not an activation function.
- ✗
K-means
Why it's wrong here
K-means is a clustering algorithm.
- ✓
ReLU
Why this is correct
ReLU is the most common activation for hidden layers.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Sigmoid
Why this is correct
Sigmoid is a classic activation function for output layers.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
CompTIA AI often tests the distinction between machine learning algorithms (like Linear Regression, SVM, K-means) and neural network components (like activation functions), so candidates mistakenly select algorithms as activation functions because they recognize them as common ML terms.
Detailed technical explanation
How to think about this question
ReLU's derivative is 0 for negative inputs and 1 for positive inputs, which allows gradients to flow effectively through deep networks during backpropagation, avoiding saturation issues seen with sigmoid or tanh. However, ReLU can suffer from 'dying ReLU' where neurons become permanently inactive if they always receive negative inputs, leading to zero gradients. In practice, variants like Leaky ReLU or Parametric ReLU are used to address this, but standard ReLU remains a foundational activation function.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
Quick reference
OSI Model Reference
| Layer | Name | PDU | Key Protocols / Devices |
|---|---|---|---|
| 7 | Application | Data | HTTP, HTTPS, DNS, SMTP, FTP, SSH |
| 6 | Presentation | Data | TLS / SSL, JPEG, ASCII encoding |
| 5 | Session | Data | NetBIOS, RPC, SIP |
| 4 | Transport | Segment / Datagram | TCP, UDP |
| 3 | Network | Packet | IP, ICMP, OSPF — Routers |
| 2 | Data Link | Frame | Ethernet, Wi-Fi, PPP — Switches, Bridges |
| 1 | Physical | Bits | Cables, NICs, Hubs, Repeaters |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AI0-001 question test?
Machine Learning and Deep Learning — This question tests Machine Learning and Deep Learning — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: ReLU — ReLU (Rectified Linear Unit) is a common activation function in deep neural networks because it introduces non-linearity while being computationally efficient, outputting the input directly if positive and zero otherwise. It helps mitigate the vanishing gradient problem, making it a default choice for hidden layers in many architectures.
What should I do if I get this AI0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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.
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