Learning Path
Question & Answer1
Understand Question2
Review Options3
Learn Explanation4
Explore TopicChoose the Best Answer
A
Image Classification
B
Text Generation
C
Time Series Analysis
D
Speech Recognition
Understanding the Answer
Let's break down why this is correct
Answer
Recurrent Neural Networks are designed to handle data that has a temporal order, so they are naturally used for sequence prediction tasks such as language modeling or speech recognition. Convolutional Neural Networks, on the other hand, are built to detect spatial patterns and are therefore most useful for image‑related tasks like image classification or object detection. The key idea is that RNNs slide a recurrent unit over a sequence, while CNNs slide convolutional filters over an image’s grid. For example, a CNN can take a 224×224 pixel picture of a cat and, by applying many filters, decide that the image contains a cat, achieving image classification.
Detailed Explanation
CNNs use tiny filters that slide over an image and detect local shapes. Other options are incorrect because Text generation is a task for RNNs, because RNNs remember past words; Time series data needs memory of previous points.
Key Concepts
Recurrent Neural Networks (RNN)
Convolutional Neural Networks (CNN)
Sequence Modeling
Topic
Recurrent Neural Networks (RNN)
Difficulty
medium level question
Cognitive Level
understand
Practice Similar Questions
Test your understanding with related questions
1
Question 1In the context of financial forecasting, how can Recurrent Neural Networks (RNNs) be effectively utilized for sequence prediction in business intelligence applications?
hardComputer-science
Practice
2
Question 2Which of the following statements are true regarding Recurrent Neural Networks (RNNs)? Select all that apply.
easyComputer-science
Practice
3
Question 3What is the primary reason recurrent neural networks (RNNs) are particularly suited for sequence modeling tasks?
easyComputer-science
Practice
4
Question 4In the context of financial forecasting, how can Recurrent Neural Networks (RNNs) be effectively utilized for sequence prediction in business intelligence applications?
hardComputer-science
Practice
5
Question 5Recurrent Neural Networks (RNN) : Sequence Prediction :: Convolutional Neural Networks (CNN) : ?
mediumComputer-science
Practice
6
Question 6Which of the following statements are true regarding Recurrent Neural Networks (RNNs)? Select all that apply.
easyComputer-science
Practice
7
Question 7What is the primary reason recurrent neural networks (RNNs) are particularly suited for sequence modeling tasks?
easyComputer-science
Practice
Ready to Master More Topics?
Join thousands of students using Seekh's interactive learning platform to excel in their studies with personalized practice and detailed explanations.