A perceptron is a type of artificial neuron that is mathematical and programmatic. It takes in many inputs and applies weights to them based on the importance of the inputs, and then adds a bias before using this mathematical approach to figure out a result. This result from the perceptron is then fed to a machine learning algorithm, such as logistic regression. We call this algorithm as an activation function, which is then is used to predict the final result of the outcome.
The perceptron is depicted as follows:
As you can see in the previous image, a perceptron depicts an artificial neuron that takes in various inputs in binary form and multiplies them with a weight, w. The weight is calculated based on the importance of the input. A bias value is also added, along with the weights. Now, the entire combination is summed up by the perceptron. Finally, the summed-up output is tested against a threshold value, and we call this as an Activation Function. If the value is above a threshold...
