What are the differences between various types of neural networks?

What are the differences between various types of neural networks?

There are several types of neural networks, including feedforward, convolutional, and recurrent neural networks. Each serves different purposes.

Can you explain feedforward neural networks?

Feedforward neural networks are the simplest type, where data moves in one direction—from input to output—without cycles.

What about convolutional neural networks?

Convolutional neural networks (CNNs) are primarily used for image processing. They use convolutional layers to detect features.

And recurrent neural networks?

Recurrent neural networks (RNNs) are designed for sequential data, allowing information to persist, making them great for tasks like language modeling.

Which one is best for natural language processing?

RNNs and their variants, like LSTMs and GRUs, are often used for natural language processing due to their ability to handle sequences.