What is Neural Network
A neural network is a computer model inspired by the human brain. Your brain is better than any modern computer, even with all the powerful (LLMs) language models out there. While neural networks are good at solving complex problems and recognizing patterns, they are still not as good as the human brain.
A neural network has layers of interconnected nodes called neurons, like in a human brain. Each connection, called a synapse, has weights that can be adjusted during training. A typical neural network has an input layer, one or more hidden layers, and an output layer.
The training process involves adjusting the weights to minimize the difference between predicted and actual outputs, often using matrix multiplication. If you remember learning about matrices in school, this is where they come into play. Feedforward neural networks use matrices to represent and process information. You multiply these matrices to get the outputs, and that is pretty much what a neural network does.
One advanced type of neural network is the spiking neural network, which mirrors the way the human brain works more closely. In these networks, neurons fire spikes when certain thresholds are reached, and the timing of these spikes is crucial. This design makes spiking neural networks more efficient in learning new things at a lower cost while maintaining good performance.
