{"id":65358,"date":"2021-04-28T15:30:35","date_gmt":"2021-04-28T14:30:35","guid":{"rendered":"https:\/\/multi.datascientest.com\/?p=65358"},"modified":"2023-10-30T18:30:47","modified_gmt":"2023-10-30T17:30:47","slug":"all-about-deep-learning","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/all-about-deep-learning","title":{"rendered":"Deep Learning: All about this concept"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"65358\" class=\"elementor elementor-65358\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f4d9127 e-flex e-con-boxed e-con\" data-id=\"f4d9127\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d47506f elementor-widget elementor-widget-text-editor\" data-id=\"d47506f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><span style=\"font-weight: 400;\">This article is the first in a series dedicated to Deep Learning: After a general introduction to the functioning and applications of neural networks, you will discover in the following articles the main types of networks and their architectures, as well as methods and various examples of applications of Deep Learning today.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Let&#8217;s start our Introduction to <strong>Deep Learning.<\/strong><\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-483c06d e-flex e-con-boxed e-con\" data-id=\"483c06d\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c3cc8ef elementor-widget elementor-widget-heading\" data-id=\"c3cc8ef\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h3 class=\"elementor-heading-title elementor-size-default\">Key concepts: AI, Machine Learning, and Deep Learning<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a3d8b61 elementor-widget elementor-widget-text-editor\" data-id=\"a3d8b61\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>In recent years, a new lexicon related to the emergence of <span style=\"text-decoration: underline;\"><a href=\"https:\/\/datascientest.com\/en\/artificial-intelligence-definition\"><strong>artificial intelligence<\/strong><\/a><\/span> in our society has flooded scientific articles, and it is sometimes <strong>difficult<\/strong> to understand what it is. When we talk about artificial intelligence, we often refer to associated technologies such as <span style=\"text-decoration: underline;\"><a href=\"https:\/\/datascientest.com\/en\/machine-learning-what-is-it-and-why-does-it-change-the-world\"><strong>machine learning<\/strong><\/a><\/span> or <strong>deep learning<\/strong>. Two terms that are extremely used with more and more applications, but not always <strong>well-defined<\/strong>. To begin, let&#8217;s go back to these <strong>three essential definitions<\/strong>.<\/p><ul><li><strong>Artificial intelligence<\/strong>: is a field of research that groups together all the techniques and methods that tend to understand and reproduce the functioning of a human brain.<\/li><li><strong>Machine Learning<\/strong>: is a set of techniques that give machines the ability to automatically learn a set of rules from data. Unlike programming, which consists of executing predetermined rules.<\/li><li><strong>Deep Learning<\/strong> : is a <strong>machine learning<\/strong> <b>technique<\/b> based on the <strong>neural network<\/strong> <b>model<\/b>: dozens or even hundreds of layers of neurons are stacked to bring more complexity to the establishment of rules.<\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-70b285d elementor-widget elementor-widget-spacer\" data-id=\"70b285d\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-column .elementor-spacer-inner{height:var(--spacer-size)}.e-con{--container-widget-width:100%}.e-con-inner>.elementor-widget-spacer,.e-con>.elementor-widget-spacer{width:var(--container-widget-width,var(--spacer-size));--align-self:var(--container-widget-align-self,initial);--flex-shrink:0}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container,.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer,.e-con>.elementor-widget-spacer>.elementor-widget-container,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer{height:100%}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner{height:var(--container-widget-height,var(--spacer-size))}<\/style>\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-c1a19ab e-flex e-con-boxed e-con\" data-id=\"c1a19ab\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f765ebb elementor-widget elementor-widget-heading\" data-id=\"f765ebb\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Machine Learning: Supervised and unsupervised learning<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d94175d elementor-widget elementor-widget-text-editor\" data-id=\"d94175d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><a href=\"https:\/\/datascientest.com\/en\/machine-learning-what-is-it-and-why-does-it-change-the-world\"><span style=\"font-weight: 400;\"><span style=\"text-decoration: underline;\"><strong>Machine Learning<\/strong><\/span><\/span><\/a><span style=\"font-weight: 400;\"> is a set of techniques that give machines the ability to learn, as opposed to programming, which consists of the execution of predetermined rules.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">There are <\/span><b>two main types of learning in Machine Learning<\/b><span style=\"font-weight: 400;\">. Supervised and unsupervised learning.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">In <\/span><b>supervised learning<\/b><span style=\"font-weight: 400;\">, the algorithm is guided with prior knowledge of what the output values of the model should be. As a result, the model <\/span><b>adjusts its parameters<\/b><span style=\"font-weight: 400;\"> in order to reduce the difference between the results obtained and the expected results. The margin of error is thus <\/span><b>reduced<\/b><span style=\"font-weight: 400;\"> as the model is trained, in order to be able to apply it to new cases.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5172158 elementor-widget elementor-widget-image\" data-id=\"5172158\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"480\" height=\"320\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/09\/DL-1.gif\" class=\"attachment-large size-large wp-image-104309\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Convergence of a model - Supervised learning<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0a79e3c elementor-widget elementor-widget-text-editor\" data-id=\"0a79e3c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">On the other hand, unsupervised learning does not use labeled data. It is then impossible for the algorithm to compute a success score with <\/span><b>certainty<\/b><span style=\"font-weight: 400;\">. Its objective is therefore to <\/span><b>deduce the clusters<\/b><span style=\"font-weight: 400;\"> present in our data. Let&#8217;s take the example of a data set of flowers, we want to group them into classes. Here, we do not know the species of the plant, but we want to try to <\/span><b>group them<\/b><span style=\"font-weight: 400;\">, for example, if the shapes of the flowers are similar then they are related to the same corresponding plant.<\/span><\/p><p><span style=\"font-weight: 400;\">There are <\/span><b>two main areas<\/b><span style=\"font-weight: 400;\"> of models in unsupervised learning to find groupings:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Partitioning methods<\/b><span style=\"font-weight: 400;\">: k-means algorithms.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Hierarchical clustering methods<\/b><span style=\"font-weight: 400;\">: hierarchical ascending classification (HAC)<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2dff620 elementor-widget elementor-widget-image\" data-id=\"2dff620\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"480\" height=\"480\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/09\/DL-2.gif.pagespeed.ce_.sPGY6AGTSh.gif\" class=\"attachment-large size-large wp-image-104310\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">K-means with k=3<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5c73918 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"5c73918\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">More informations about our Data courses<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d016f72 e-flex e-con-boxed e-con\" data-id=\"d016f72\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-060cd0d elementor-widget elementor-widget-heading\" data-id=\"060cd0d\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What is Deep Learning?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-71feb4c elementor-widget elementor-widget-spacer\" data-id=\"71feb4c\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d800461 elementor-widget__width-initial elementor-widget elementor-widget-image\" data-id=\"d800461\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"450\" src=\"https:\/\/datascientest.com\/en\/files\/2021\/04\/deep_learning-1.jpg\" class=\"attachment-large size-large wp-image-166414\" alt=\"what-is-deep-learning\" srcset=\"https:\/\/datascientest.com\/en\/files\/2021\/04\/deep_learning-1.jpg 800w, https:\/\/datascientest.com\/en\/files\/2021\/04\/deep_learning-1-300x169.jpg 300w, https:\/\/datascientest.com\/en\/files\/2021\/04\/deep_learning-1-768x432.jpg 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1438c0b elementor-widget elementor-widget-spacer\" data-id=\"1438c0b\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-324a43b elementor-widget elementor-widget-text-editor\" data-id=\"324a43b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Deep learning is <\/span><b>one of the main technologies <\/b><span style=\"font-weight: 400;\">of machine learning. With Deep Learning, we are talking about <\/span><b>algorithms<\/b><span style=\"font-weight: 400;\"> capable of mimicking the actions of the human brain thanks to artificial neural networks.\u00a0 The networks are composed of <\/span><b>dozens or even hundreds of &#8220;layers&#8221; of neurons<\/b><span style=\"font-weight: 400;\">, each receiving and interpreting the information of the previous layer.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-29356c9 elementor-widget elementor-widget-image\" data-id=\"29356c9\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"396\" src=\"https:\/\/datascientest.com\/en\/files\/2021\/04\/Linear-models-1024x507.jpg\" class=\"attachment-large size-large wp-image-166415\" alt=\"linear-non-linear-models\" srcset=\"https:\/\/datascientest.com\/en\/files\/2021\/04\/Linear-models-1024x507.jpg 1024w, https:\/\/datascientest.com\/en\/files\/2021\/04\/Linear-models-300x149.jpg 300w, https:\/\/datascientest.com\/en\/files\/2021\/04\/Linear-models-768x381.jpg 768w, https:\/\/datascientest.com\/en\/files\/2021\/04\/Linear-models.jpg 1457w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a46a9e4 elementor-widget elementor-widget-text-editor\" data-id=\"a46a9e4\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Each <\/span><b>artificial neuron<\/b><span style=\"font-weight: 400;\"> represented in the previous image by a circle, can be seen as a linear model. By interconnecting the neurons in a layer, we transform our neural network into a <\/span><b>very complex<\/b><span style=\"font-weight: 400;\"> non-linear model.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f0c32b0 elementor-widget elementor-widget-image\" data-id=\"f0c32b0\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"394\" height=\"214\" src=\"https:\/\/datascientest.com\/en\/files\/2021\/04\/DL3-1024x614-1.webp\" class=\"attachment-large size-large wp-image-166416\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2021\/04\/DL3-1024x614-1.webp 394w, https:\/\/datascientest.com\/en\/files\/2021\/04\/DL3-1024x614-1-300x163.webp 300w\" sizes=\"(max-width: 394px) 100vw, 394px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4c43e33 elementor-widget elementor-widget-text-editor\" data-id=\"4c43e33\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">To illustrate the concept, let&#8217;s take a <\/span><b>problem of classification<\/b><span style=\"font-weight: 400;\"> between a dog and a cat from images. During the learning process, the algorithm will <\/span><b>adjust the weights<\/b> <b>of the neurons<\/b><span style=\"font-weight: 400;\"> in order to reduce the gap between the results obtained and the expected results. The model will be able to <\/span><b>learn to detect<\/b><span style=\"font-weight: 400;\"> triangles in an image, since cats have much more triangular ears than dogs.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-515077f elementor-widget elementor-widget-spacer\" data-id=\"515077f\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-93571c9 e-flex e-con-boxed e-con\" data-id=\"93571c9\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f8a4bdc elementor-widget elementor-widget-heading\" data-id=\"f8a4bdc\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What is Deep Learning used for?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-700d8ad elementor-widget elementor-widget-text-editor\" data-id=\"700d8ad\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Deep learning models tend to work well with <\/span><b>large amounts of data<\/b><span style=\"font-weight: 400;\">, whereas more traditional machine learning models stop improving after a saturation point.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1f76865 elementor-widget elementor-widget-image\" data-id=\"1f76865\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"577\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/DL5.png\" class=\"attachment-large size-large wp-image-3131\" alt=\"Deep learning\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/DL5.png 805w, https:\/\/datascientest.com\/en\/files\/2020\/06\/DL5-300x217.png 300w, https:\/\/datascientest.com\/en\/files\/2020\/06\/DL5-768x554.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f9caf7c elementor-widget elementor-widget-spacer\" data-id=\"f9caf7c\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-34e0dfc elementor-widget elementor-widget-text-editor\" data-id=\"34e0dfc\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Over the years, with the emergence of Big Data and increasingly <\/span><b>powerful computer components<\/b><span style=\"font-weight: 400;\">, power- and <strong>data-hungry Deep Learning algorithms<\/strong> have outpaced most other methods. They seem to be ready to solve <\/span><b>many problems<\/b><span style=\"font-weight: 400;\">: recognizing faces, defeating poker or go players, enabling the driving of autonomous cars or even searching for cancer cells.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5c465f7 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"5c465f7\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/appointment\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Book an appointment with DataScientest<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e67995a e-flex e-con-boxed e-con\" data-id=\"e67995a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-15da992 elementor-widget elementor-widget-heading\" data-id=\"15da992\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">AI in the professional World<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7398c59 elementor-widget elementor-widget-text-editor\" data-id=\"7398c59\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Almost every industry is affected by <\/span><b>AI. Machine Learning<\/b><span style=\"font-weight: 400;\"> and <\/span><b>Deep Learning<\/b><span style=\"font-weight: 400;\"> play a big role in this.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Whether you are a medical professional or a lawyer, it is possible that one day a highly autonomous model will assist you or even replace you. In the <\/span><b>healthcare industry<\/b><span style=\"font-weight: 400;\">, there are already applications to automatically diagnose a patient.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2686651 elementor-widget elementor-widget-image\" data-id=\"2686651\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"511\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/DL6-1024x654.jpg\" class=\"attachment-large size-large wp-image-3130\" alt=\"Deep Learning\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/DL6-1024x654.jpg 1024w, https:\/\/datascientest.com\/en\/files\/2020\/06\/DL6-300x192.jpg 300w, https:\/\/datascientest.com\/en\/files\/2020\/06\/DL6-768x491.jpg 768w, https:\/\/datascientest.com\/en\/files\/2020\/06\/DL6.jpg 1280w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Automatic detection of a fracture using Deep Learning<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-189d500 elementor-widget elementor-widget-text-editor\" data-id=\"189d500\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The <\/span><b>automotive industry<\/b><span style=\"font-weight: 400;\"> is also being shaken up with the arrival of assisted driving.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-10cd65e elementor-widget elementor-widget-image\" data-id=\"10cd65e\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"540\" height=\"304\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/DL7.gif\" class=\"attachment-large size-large wp-image-3129\" alt=\"deep learning\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fdb23c0 elementor-widget elementor-widget-text-editor\" data-id=\"fdb23c0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">It is also thanks to deep Learning that <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/www.deepmind.com\/research\/highlighted-research\/alphago\">Google&#8217;s Alpha Go model<\/a><\/strong><\/span><span style=\"font-weight: 400;\"> managed to beat the best Go champions in 2016. The search engine of the American giant is itself increasingly based on deep learning rather than on written rules.<\/span><\/p><p><span style=\"font-weight: 400;\">Today, deep learning is even capable of &#8220;<\/span><b>creating&#8221; paintings<\/b><span style=\"font-weight: 400;\"> by itself. This is called <\/span><b>Style Transfer<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bdeaa2d elementor-widget elementor-widget-image\" data-id=\"bdeaa2d\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"512\" height=\"305\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/DL8.jpg\" class=\"attachment-large size-large wp-image-3128\" alt=\"style transfer deep learning\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/DL8.jpg 512w, https:\/\/datascientest.com\/en\/files\/2020\/06\/DL8-300x179.jpg 300w\" sizes=\"(max-width: 512px) 100vw, 512px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Style transfer<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c837737 elementor-widget elementor-widget-text-editor\" data-id=\"c837737\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">In the following part of the article, we will introduce you to <\/span><b>neural networks<\/b><span style=\"font-weight: 400;\"> with a new approach, we hope you will appreciate it!\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0caf31e elementor-widget elementor-widget-spacer\" data-id=\"0caf31e\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-406309c e-flex e-con-boxed e-con\" data-id=\"406309c\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d9baa57 elementor-widget elementor-widget-heading\" data-id=\"d9baa57\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Deep Learning as a solution in e-commerce<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ea94821 elementor-widget elementor-widget-heading\" data-id=\"ea94821\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h5 class=\"elementor-heading-title elementor-size-default\">AI analysis used in e-commerce<\/h5>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-98d60d2 elementor-widget elementor-widget-text-editor\" data-id=\"98d60d2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">It is obvious that the <\/span><b>e-commerce industry generates large amounts of data<\/b><span style=\"font-weight: 400;\">. Companies, merchants and retailers are aware that Big Data solutions to manage their operations will make their business <\/span><b>more valuable<\/b><span style=\"font-weight: 400;\">. Despite the irruption of all these innovative solutions, Big Data can be a blessing or a curse, depending on how it is used and applied.<\/span><\/p><p><span style=\"font-weight: 400;\">The <\/span><b>artificial intelligence revolution<\/b><span style=\"font-weight: 400;\"> aims to make it easier to manage this huge amount of data, thanks to intelligent technologies such as deep learning. It is <\/span><b>essential<\/b><span style=\"font-weight: 400;\"> because it provides elements for better data analysis.<\/span><\/p><p><span style=\"font-weight: 400;\">In a practical case,<\/span><b> AI analysis<\/b><span style=\"font-weight: 400;\"> makes it easier for an online store to offer interesting products to its customers, to highlight their preferences and to provide them with personalized attention. Deep learning <\/span><b>automates <\/b><span style=\"font-weight: 400;\">what is known as predictive analysis. With this, customers can <\/span><b>receive suggestions<\/b><span style=\"font-weight: 400;\"> when making a purchase.<\/span><\/p><p><span style=\"font-weight: 400;\">Deep learning defines a style when it comes to e-commerce. It is not about <\/span><b>creating online sites<\/b><span style=\"font-weight: 400;\"> that attract large proportions of buyers. The goal is to send clear, individualized messages to each of them.<\/span><\/p><p><b>Big Data<\/b><span style=\"font-weight: 400;\"> is subjected to deep analysis through deep learning, which leads to facilitating the buying process of customers. <\/span><b>Deep learning algorithms<\/b><span style=\"font-weight: 400;\"> help the company to get a better experience and keep track of those who have visited its site.<\/span><\/p><p><span style=\"font-weight: 400;\">Deep learning is coming in to <\/span><b>facilitate the expansion<\/b><span style=\"font-weight: 400;\"> of e-commerce. Online sales are being driven by <\/span><b>technology trends<\/b><span style=\"font-weight: 400;\"> such as chatbots.<\/span><\/p><p><span style=\"font-weight: 400;\">In a way, Deep Learning is <\/span><b>redefining online commerce<\/b><span style=\"font-weight: 400;\">, and we&#8217;re still in its infancy. Therefore, those who adopt it will have more advantages.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c5e0c5c elementor-widget elementor-widget-heading\" data-id=\"c5e0c5c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h5 class=\"elementor-heading-title elementor-size-default\">Deep Learning and neural networks: biological or artificial?<\/h5>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5be7d8b elementor-widget elementor-widget-text-editor\" data-id=\"5be7d8b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Before tackling the <strong>precise functioning<\/strong> of neural networks, we thought it would be interesting to <strong>draw a parallel<\/strong> with biological neurons.\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-b6ca46b e-flex e-con-boxed e-con\" data-id=\"b6ca46b\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ccc98fc elementor-widget elementor-widget-heading\" data-id=\"ccc98fc\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Biological neuron : Structure and role<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bd50cd8 elementor-widget elementor-widget-text-editor\" data-id=\"bd50cd8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The nervous system is composed of <\/span><b>billions of cells<\/b><span style=\"font-weight: 400;\">: it is a <\/span><b>network of biological neurons<\/b><span style=\"font-weight: 400;\">. In fact, neurons are not independent of each other, they establish links between them and form more or less complex networks.<\/span><\/p><p><span style=\"font-weight: 400;\">\u00a0The <\/span><b>biological neuron<\/b><span style=\"font-weight: 400;\"> is composed of three main parts:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The <\/span><b>cell body<\/b><span style=\"font-weight: 400;\"> is composed of the control center processing the information received by the dendrites.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The <\/span><b>dendrites <\/b><span style=\"font-weight: 400;\">are the main wires through which the information coming from the outside passes.\u00a0<\/span><\/li><\/ul><p><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">The <\/span><b style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">axon <\/b><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">is the conducting wire that leads the output signal from the cell body to other neurons.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c7e5c30 elementor-widget elementor-widget-image\" data-id=\"c7e5c30\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"450\" src=\"https:\/\/datascientest.com\/en\/files\/2021\/04\/DL5-1024x576.jpg\" class=\"attachment-large size-large wp-image-166417\" alt=\"Biological neuron\" srcset=\"https:\/\/datascientest.com\/en\/files\/2021\/04\/DL5-1024x576.jpg 1024w, https:\/\/datascientest.com\/en\/files\/2021\/04\/DL5-300x169.jpg 300w, https:\/\/datascientest.com\/en\/files\/2021\/04\/DL5-768x432.jpg 768w, https:\/\/datascientest.com\/en\/files\/2021\/04\/DL5-1536x864.jpg 1536w, https:\/\/datascientest.com\/en\/files\/2021\/04\/DL5.jpg 1920w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c688658 elementor-widget elementor-widget-text-editor\" data-id=\"c688658\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">As for <\/span><b>synapses<\/b><span style=\"font-weight: 400;\">, they act as links and weights between neurons and therefore allow neurons to communicate with each other.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a6e53f5 elementor-widget elementor-widget-image\" data-id=\"a6e53f5\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"586\" height=\"432\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.32.51.png\" class=\"attachment-large size-large wp-image-3659\" alt=\"neurones biologique\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.32.51.png 586w, https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.32.51-300x221.png 300w\" sizes=\"(max-width: 586px) 100vw, 586px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-075718e elementor-widget elementor-widget-spacer\" data-id=\"075718e\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-945a2c6 e-flex e-con-boxed e-con\" data-id=\"945a2c6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ba373a9 elementor-widget elementor-widget-heading\" data-id=\"ba373a9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What is the link between biological and artificial neurons?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-649fd74 elementor-widget elementor-widget-text-editor\" data-id=\"649fd74\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">In summary:<\/span><\/p><p><span style=\"font-weight: 400;\">Biological neurons have a <\/span><b>control center<\/b><span style=\"font-weight: 400;\"> (called a somatic cell) that sums up the information collected by the dendrites. Then, the control center returns an action potential according to the following rules:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">If the <\/span><b>input sum<\/b> <b>does not exceed<\/b><span style=\"font-weight: 400;\"> the excitation threshold: no nerve message via the axon.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">If the <\/span><b>input sum<\/b> <b>exceeds<\/b><span style=\"font-weight: 400;\"> the excitation threshold: a nerve message is sent via the axon (this is the idea, but in reality a little <\/span><b>more complicated<\/b><span style=\"font-weight: 400;\">).<\/span><\/li><\/ul><p>\u00a0<\/p><p><span style=\"font-weight: 400;\">Let&#8217;s proceed to a simple comparison of the main steps of the perceptron algorithm with the constitutive elements of biological neurons. This choice of algorithm is <\/span><b>justified<\/b><span style=\"font-weight: 400;\"> because it is as close as possible to the functioning of biological neurons:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Synapses\/dendrites<\/b><span style=\"font-weight: 400;\">: weighting of each element in input wi. xi<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Cell bodies<\/b><span style=\"font-weight: 400;\">: application of an activation function f to the sum of the weighted inputs<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Axon<\/b><span style=\"font-weight: 400;\">: output of our model<\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a87367f elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"a87367f\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/data-courses\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Discover DataScientest's training courses<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96a142f elementor-widget elementor-widget-image\" data-id=\"96a142f\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"574\" height=\"126\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.16.08.png\" class=\"attachment-large size-large wp-image-3656\" alt=\"formula\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.16.08.png 574w, https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.16.08-300x66.png 300w\" sizes=\"(max-width: 574px) 100vw, 574px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-32213aa elementor-widget elementor-widget-image\" data-id=\"32213aa\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"249\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/content_content_neuron.png\" class=\"attachment-large size-large wp-image-3655\" alt=\"neuron\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/content_content_neuron.png 800w, https:\/\/datascientest.com\/en\/files\/2020\/06\/content_content_neuron-300x93.png 300w, https:\/\/datascientest.com\/en\/files\/2020\/06\/content_content_neuron-768x239.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2d94543 elementor-widget elementor-widget-text-editor\" data-id=\"2d94543\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The specific vocabulary for this algorithm is as follows:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The vector w is called the <\/span><b>weight vector<\/b><span style=\"font-weight: 400;\"> (which adjusts during training).<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The vector x is called the<\/span><b> input vector<\/b><span style=\"font-weight: 400;\">.<\/span><\/li><\/ul><p><b><i>f <\/i><\/b><span style=\"font-weight: 400;\">is referred to as the activation function.<\/span><\/p><p><span style=\"font-weight: 400;\">For most activation functions, the <\/span><b>perceptron<\/b><span style=\"font-weight: 400;\"> consists of finding the <\/span><b>separating hyperplane<\/b><span style=\"font-weight: 400;\"> (defined by w) between our two classes:<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b171133 elementor-widget__width-initial elementor-widget elementor-widget-image\" data-id=\"b171133\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"676\" height=\"616\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.17.07.png\" class=\"attachment-large size-large wp-image-3657\" alt=\"Perceptron-algorithm\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.17.07.png 676w, https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.17.07-300x273.png 300w\" sizes=\"(max-width: 676px) 100vw, 676px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f6632a6 elementor-widget elementor-widget-text-editor\" data-id=\"f6632a6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The <\/span><b>simple Perceptron algorithm<\/b><span style=\"font-weight: 400;\"> is no longer used in practice, since other algorithms such as the Support Vector Machine are much more efficient. Also,<\/span><b> biological neurons<\/b><span style=\"font-weight: 400;\"> are not used individually, they are usually linked to other neurons.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0a2235b elementor-widget__width-initial elementor-widget elementor-widget-image\" data-id=\"0a2235b\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"500\" height=\"528\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/500px-Neurons_big1.jpg\" class=\"attachment-large size-large wp-image-3654\" alt=\"neurons\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/500px-Neurons_big1.jpg 500w, https:\/\/datascientest.com\/en\/files\/2020\/06\/500px-Neurons_big1-284x300.jpg 284w\" sizes=\"(max-width: 500px) 100vw, 500px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-932d71d elementor-widget elementor-widget-text-editor\" data-id=\"932d71d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The interest in the Perceptron algorithm comes from a technique demonstrated in 1989 by <\/span><b>George Cybenko<\/b><span style=\"font-weight: 400;\"> which consists in linking and stacking layers of perceptron to bring more complexity. An algorithm of this type is called <\/span><b>Multilayer Perceptron<\/b><span style=\"font-weight: 400;\"> (MLP).<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c68444f elementor-widget elementor-widget-image\" data-id=\"c68444f\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"355\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.18.36-1024x454.png\" class=\"attachment-large size-large wp-image-3658\" alt=\"Multilayer Perceptron\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.18.36-1024x454.png 1024w, https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.18.36-300x133.png 300w, https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.18.36-768x340.png 768w, https:\/\/datascientest.com\/en\/files\/2020\/06\/Capture-d\u2019e\u0301cran-2020-06-12-a\u0300-13.18.36.png 1178w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6daac29 elementor-widget elementor-widget-text-editor\" data-id=\"6daac29\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">In the previous figure, the model consists of classifying (in 10 classes) images of handwritten figures. The green squares are the <\/span><b>inputs<\/b><span style=\"font-weight: 400;\"> of our model, the <\/span><b>perceptrons<\/b><span style=\"font-weight: 400;\"> are represented by gray circles and the links are represented by the arrows.<\/span><\/p><p><span style=\"font-weight: 400;\">In general, the last layer of our model is used to format the desired result. Here, as we have a classification problem, we want to <\/span><b>predict the probability of each class<\/b><span style=\"font-weight: 400;\"> (number 0, number 1 &#8230;). This is why the last layer has 10 neurons since there are 10 classes, and a &#8220;<\/span><b>softmax<\/b><span style=\"font-weight: 400;\">&#8221; activation function allowing it to return a probability.<\/span><\/p><p><span style=\"font-weight: 400;\">It is much freer for the other layers of our model, it is especially important that the <\/span><b>activation functions<\/b><span style=\"font-weight: 400;\"> of the perceptrons are non-linear to make the model more complex. In practice, the <\/span><b>tanh<\/b><span style=\"font-weight: 400;\"> or <\/span><b>ReLU activation<\/b><span style=\"font-weight: 400;\"> functions are the most used.<\/span><\/p><p><span style=\"font-weight: 400;\">Like for LEGO\u2019s, it is up to the <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/datascientest.com\/en\/how-to-become-a-data-scientist\">Data Scientist<\/a><\/strong><\/span><span style=\"font-weight: 400;\"> to choose the architecture of his model.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-983a918 elementor-widget elementor-widget-image\" data-id=\"983a918\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"300\" src=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/pile21-14749-a6581-e3a3f.png\" class=\"attachment-large size-large wp-image-3653\" alt=\"Perceptron lego\" srcset=\"https:\/\/datascientest.com\/en\/files\/2020\/06\/pile21-14749-a6581-e3a3f.png 300w, https:\/\/datascientest.com\/en\/files\/2020\/06\/pile21-14749-a6581-e3a3f-150x150.png 150w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-85d8f51 elementor-widget elementor-widget-text-editor\" data-id=\"85d8f51\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">There are architectures that are <\/span><b>more efficient <\/b><span style=\"font-weight: 400;\">than others, but there is no real mathematical rule behind them. It is the experience that prevails on the choice of the model structures.<\/span><\/p><p><span style=\"font-weight: 400;\">Sources :<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">F. Rosenblatt (1958), <\/span><span style=\"text-decoration: underline;\"><a href=\"http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.335.3398&amp;rep=rep1&amp;type=pdf\"><i><span style=\"font-weight: 400;\">The perceptron: a probabilistic model for information storage and organization in the brain<\/span><\/i><\/a><\/span><\/li><li><span style=\"font-weight: 400;\">G. Cybenkot (1989), <\/span><span style=\"text-decoration: underline;\"><a href=\"http:\/\/cognitivemedium.com\/magic_paper\/assets\/Cybenko.pdf\"><i><span style=\"font-weight: 400;\">Approximation by Superpositions of a Sigmoidal Function<\/span><\/i><\/a><\/span><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-baa1cf7 e-flex e-con-boxed e-con\" data-id=\"baa1cf7\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4b17c29 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"4b17c29\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Discover the Machine Learning Engineer training <\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-54e854f e-flex e-con-boxed e-con\" data-id=\"54e854f\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6683688 elementor-widget elementor-widget-html\" data-id=\"6683688\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"What is Deep Learning?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Deep learning is one of the main technologies of machine learning. 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