{"id":203,"date":"2018-01-05T10:47:00","date_gmt":"2018-01-05T09:47:00","guid":{"rendered":"https:\/\/kindsonthegenius.com\/blog\/2018\/01\/05\/what-is-perceptron-how-the-perceptron-works\/"},"modified":"2020-08-22T11:11:38","modified_gmt":"2020-08-22T09:11:38","slug":"what-is-perceptron-how-the-perceptron-works","status":"publish","type":"post","link":"https:\/\/kindsonthegenius.com\/blog\/what-is-perceptron-how-the-perceptron-works\/","title":{"rendered":"What is Perceptron? How the Perceptron Works"},"content":{"rendered":"
\n
Today we will understand the concept of Perceptron.<\/p>\n

Basics of The Perceptron<\/b>
The perceptron(or single-layer perceptron) is the simplest model of a neuron that illustrates how a neural network works. The perceptron is a machine learning algorithm developed in 1957 by Frank Rosenblatt and first implemented in IBM 704.<\/p>\n

The perceptron is a network that takes a number of inputs, carries out some processing on those inputs and produces an output as can be shown in Figure 1. <\/p>\n\n\n\n\n
<\/a><\/td>\n<\/tr>\n
Figure 1: How the Perceptron Works<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

How the Perceptron Works<\/i><\/b>
How the perceptron works is illustrated in Figure 1.  In the example, the perceptron has three inputs x1<\/sub>, x2<\/sub><\/i> and x3<\/sub><\/i> and one output.
The importance of this inputs is determined by the corresponding weights w1<\/sub>, w2<\/sub><\/i> and w3<\/sub><\/i> assigned to this inputs. The output could be a 0 or a 1 depending on the weighted sum of the inputs. Output is 0 if the sum is below certain threshold or 1 if the output is above certain threshold. This threshold could be a real number and a parameter of the neuron. Since the output of the perceptron could be either 0 or 1, this perceptron is an example of binary classifier.<\/p>\n

This is shown below in Equation 1<\/p>\n\n\n\n\n
<\/a><\/td>\n<\/tr>\n
Equation 1:  output of a perceptron<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 The Formula<\/b>
Let’s write out the formula that joins the inputs and the weights together to produce the output<\/p>\n

Output =<\/b> w1<\/sub>x1<\/sub> + w2<\/sub>x2<\/sub> + w3<\/sub>x3 <\/sub><\/i><\/span> <\/div>\n

This function is a trivial one, but it remains the basic formula for the perceptron but I want you to read this equation as<\/p>\n

Output ‘depends on’  w1<\/sub>x1<\/sub> + w2<\/sub>x2<\/sub> + w3<\/sub>x<\/span>3 <\/span><\/sub><\/i><\/div>\n

The reason for this is because, the output is not necessarily just a sum of these values, it may also depend on a bias that is added to this expression. In other words, we can think of a perceptron as a ‘judge who weights up several evidences together with other rules and the makes a decision’<\/p>\n

We would discuss this in detail in the Neural Networks lesson.<\/p>\n

This operation of the perceptron serves as the basics of Neural Networks and would serve as a good introduction to learning neural network which we would be examining in subsequent lessons.<\/p>\n

Now we would examine a more detailed model of a neural network, but that would be in part 2 because I need to keep this lesson as simple as possible.<\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Today we will understand the concept of Perceptron. Basics of The PerceptronThe perceptron(or single-layer perceptron) is the simplest model of a neuron that illustrates how … <\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0},"categories":[11,16],"tags":[],"_links":{"self":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/203"}],"collection":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/comments?post=203"}],"version-history":[{"count":1,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/203\/revisions"}],"predecessor-version":[{"id":1471,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/203\/revisions\/1471"}],"wp:attachment":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/media?parent=203"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/categories?post=203"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/tags?post=203"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}