Artificial Intelligence (AI) MCQs - Part 4 | TechSpark AI

 

Artificial Intelligence (AI) MCQs | TechSpark AI

(Part 4)

1. What does the term "big data" refer to in AI?

   a) Large amounts of data collected from various sources  
   b) Data that is difficult to process with traditional methods  
   c) High-quality, structured data  
   d) Data that is easy to analyze  

2. What is the role of a loss function in machine learning?

   a) To evaluate the accuracy of a model  
   b) To determine the speed of learning  
   c) To measure the difference between predicted and actual values  
   d) To increase the complexity of the model  

3. Which of the following is an AI-driven service?

   a) E-commerce websites  
   b) Online video streaming  
   c) Personalized recommendations  
   d) Digital textbooks  

4. Which of the following is a common AI technique for natural language understanding?

   a) Linear regression  
   b) Convolutional neural networks  
   c) Recurrent neural networks (RNNs)  
   d) Decision trees  

5. What is the purpose of a data scientist in AI?

   a) To build and maintain databases  
   b) To manage network security  
   c) To analyze and interpret complex data  
   d) To design user interfaces  

6. Which of the following is a method to avoid overfitting in machine learning?

   a) Decreasing data size  
   b) Increasing model complexity  
   c) Cross-validation  
   d) Reducing the number of features  

7. Which of the following is an example of AI in social media?

   a) Image filters  
   b) Predictive text  
   c) User profiling for targeted advertising  
   d) Cloud storage  

8. What is the main difference between supervised and unsupervised learning?

   a) Supervised learning requires labeled data, while unsupervised learning does not  
   b) Unsupervised learning requires labeled data, while supervised learning does not  
   c) Supervised learning is faster  
   d) Unsupervised learning is more accurate  

9. Which of the following AI techniques is best for anomaly detection?

   a) Regression analysis  
   b) Clustering  
   c) Reinforcement learning  
   d) Dimensionality reduction  

10. What does the term "AI winter" refer to?

   a) A period of rapid AI development  
   b) A time when AI research funding and interest significantly declined  
   c) A season-themed AI competition  
   d) A phase of AI where systems become self-aware