ETI PT-1

Question 1

20. What technique is used in Deep Learning to prevent overfitting and improve generalization?

Accepted Answer

a) Regularization techniques like Dropout

Question 2

16. Which type of neural network architecture is particularly designed for tasks like generating realistic images?

Accepted Answer

a) Generative Adversarial Networks (GANs)

Question 3

1. What is the primary goal of Artificial Intelligence (AI)?

Accepted Answer

b) To make machines intelligent and able to perform tasks autonomously.

Question 4

11. Deep Learning models are built using which of the following structures?

Accepted Answer

b) Neural Networks

Question 5

15. In which scenario would Recurrent Neural Networks (RNNs) be most appropriate?

Accepted Answer

c) Generating sequential text, such as speech or sentences.

Question 6

7. Which layer ensures that data is consistently interpreted across the network?

Accepted Answer

c) Semantic Layer

Question 7

5. Which blockchain layer is responsible for user interfaces and applications that interact with the blockchain?

Accepted Answer

c) Application Layer

Question 8

4. What is a primary advantage of a decentralized system like blockchain?

Accepted Answer

b) Reduced risk of censorship and single points of failure.

Question 9

10. What is a major limitation of centralized systems that blockchain aims to address?

Accepted Answer

b) Lack of transparency and trust.

Question 10

6. The "smart contracts" that automate and enforce agreements reside in which layer?

Accepted Answer

b) Execution Layer

Question 11

8. How are new blocks added to the blockchain, a process managed by which layer?

Accepted Answer

c) Consensus Layer

Question 12

12. What distinguishes Deep Learning from traditional Machine Learning?

Accepted Answer

d) DL uses neural networks with multiple layers to model complex patterns.

Question 13

2. Which of the following is a key component of AI?

Accepted Answer

d) Both b and c

Question 14

13. Which of the following is a popular architecture used for image recognition tasks in Deep Learning?

Accepted Answer

a) Convolutional Neural Networks (CNNs)

Question 15

14. What is the purpose of the "Activation Function" in a neural network?

Accepted Answer

b) To help neurons make decisions based on their input.

Question 16

8. Which of the following is an example of a Supervised Learning algorithm?

Accepted Answer

b) Decision Trees

Question 17

19. Which of the following is NOT a common application of deep learning?

Accepted Answer

c) Web scraping

Question 18

18. Which of the following is a major challenge when training deep learning models?

Accepted Answer

b) Overfitting

Question 19

1. Which of the following best describes the "backstory" of blockchain?

Accepted Answer

b) Evolved from cryptographic research and distributed systems concepts.

Question 20

3. Which field of AI focuses on making machines understand and process human languages?

Accepted Answer

b) Natural Language Processing (NLP)

Question 21

22. What is the main difference between Supervised Learning and Unsupervised Learning?

Accepted Answer

a) SL uses labeled data, while unsupervised learning uses unlabeled data.

Question 22

6. What does Machine Learning (ML) focus on?

Accepted Answer

b) Machines learning from data and improving over time.

Question 23

3. Which is a key characteristic of a centralized system?

Accepted Answer

b) A single entity controls and manages the system.

Question 24

7. In Supervised Learning, what type of data is used to train the model?

Accepted Answer

b) Labeled data

Question 25

12. Which of the following is a common use case for blockchain technology?

Accepted Answer

d) All of the above.

Question 26

9. Which layer handles the dissemination of transactions and blocks across the network?

Accepted Answer

a) Propagation Layer

Question 27

21. In Reinforcement Learning, which of the following is the agent’s goal?

Accepted Answer

a) To maximize rewards over time.

Question 28

17. What is a key feature of a Transformer Network in deep learning?

Accepted Answer

b) It can process sequences in parallel and handle long-range dependencies.

Question 29

5. Which of the following is an example of a real-world AI application?

Accepted Answer

a) Email spam filters

Question 30

4. Which of the following is NOT a type of AI?

Accepted Answer

d) Sharp AI

Question 31

10. What is the purpose of the Loss Function in machine learning?

Accepted Answer

b) To evaluate the error between the predicted output and actual output.

Question 32

9. In which machine learning technique do models learn from sequences of data to make predictions?

Accepted Answer

b) Reinforcement learning

Question 33

11. Which of the following is NOT a potential benefit of blockchain adoption?

Accepted Answer

c) Guaranteed complete anonymity in all transactions.

Question 34

2. What is the core concept behind blockchain technology?

Accepted Answer

b) A distributed, immutable ledger shared among multiple participants.

ETI PT-1

Questions 34

ETI PT-1

Questions 34