Understanding how neural networks predict
The prediction process used to generate the output value in a neural network is known as forward propagation. During this process, input values are passed through the network’s layers, where each neuron applies a mathematical operation to the data, such as multiplication by weights and the addition of biases. The result of each operation is passed to the next layer until the output is produced.
This process is essential for making predictions or decisions based on the given inputs and is a key mechanism in neural networks. Therefore, the weights of each neuron play a crucial role in the prediction process.
Imagine a turret on a battlefield tasked to defend the gate of a base from the player. The turret’s system takes two inputs:
- Distance of the player from the turret
- Angular difference required for the turret to aim at the player
Based on these inputs, the system produces an output value between...
