In a case study involving natural language processing, which type of neural network is often used?
Practice Questions
1 question
Q1
In a case study involving natural language processing, which type of neural network is often used?
Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)
Feedforward Neural Network
Radial Basis Function Network
Recurrent Neural Networks (RNNs) are commonly used in natural language processing due to their ability to handle sequential data.
Questions & Step-by-step Solutions
1 item
Q
Q: In a case study involving natural language processing, which type of neural network is often used?
Solution: Recurrent Neural Networks (RNNs) are commonly used in natural language processing due to their ability to handle sequential data.
Steps: 5
Step 1: Understand what natural language processing (NLP) is. It involves teaching computers to understand and work with human language.
Step 2: Learn about different types of neural networks. These are models that help computers learn from data.
Step 3: Identify the type of data used in NLP. This data is often sequential, meaning it comes in a specific order, like sentences in a paragraph.
Step 4: Discover that Recurrent Neural Networks (RNNs) are designed to work with sequential data. They can remember previous information, which is important for understanding language.
Step 5: Conclude that RNNs are commonly used in NLP because they can effectively process and analyze text data.
