Component of a Neural Network

The key components of a neural network encompass various elements that contribute to its functionality. Here’s a breakdown of the options provided:

Neurons and Synapses: Neurons are indeed the fundamental units of a neural network, analogous to biological neurons, and synapses represent the connections between them, usually weighted to signify their importance.

Layers and Nodes: Neural networks are structured in layers, including input, hidden, and output layers. Each layer consists of nodes (or neurons), which process inputs and pass outputs to subsequent layers.

Recurrent Units and Dropout: Recurrent units are specific to recurrent neural networks (RNNs), which are designed for sequential data. Dropout is a regularization technique used to prevent overfitting by randomly dropping units during training.

Given that all these elements play significant roles in different types of neural networks, the correct answer is: All of the above.