In this post, you will learn about **Perceptrons **with the help of a Pythonexample.It is very important for data scientists to understand the concepts related to Perceptron as a good understanding lays the foundation of learning advanced concepts of neural networks including deep neural networks (deep learning).

What Is a Perceptron?

Perceptron is a machine learning algorithm which mimics how a neuron in the brain works. It is also called as single layer neural network, as the output is decided based on the outcome of just one activation function which represents a neuron.

Let’s first understand how a neuron works. The diagram below represents a neuron in the brain. The input signals (x1, x2, …) of different strength (observe weights, w1, w2 …) is fed into the neuron cell via dendrites. The net input (weighted sum) is processed by the neuron and output signal (observer signal in AXON) is appropriately fired. In case the combined signal strength is not appropriate based on decision function within neuron cell (observe activation function), the neuron does not fire any output signal.

#python #ai #deep learning #neural network #perceptron #data-science