ANNs
Neurons are cool, right? But single neurons cannot perform complex tasks, which is why our brain has billions of neurons, organized in layers, forming a network. Similarly, artificial neurons are arranged in layers. Each and every layer will be connected in such a way that information is passed from one layer to another. A typical ANN consists of the following layers:
- Input layer
- Hidden layer
- Output layer
Each layer has a collection of neurons, and the neurons in one layer interact with all the neurons in the other layers. However, neurons in the same layer will not interact with each other. A typical ANN is shown in the following diagram:
Input layer
The input layer is where we feed input to the network. The number of neurons in the input layer is the number of inputs we feed to the network. Each input will have some influence on predicting the output and this will be multiplied by weights, while bias will be added and passed to the next layer.
Hidden layer
Any layer between the input layer...
