{"id":166192,"date":"2023-03-28T09:35:27","date_gmt":"2023-03-28T08:35:27","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=166192"},"modified":"2024-11-27T14:18:08","modified_gmt":"2024-11-27T13:18:08","slug":"deep-neural-network-what-is-it-and-how-is-it-working","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/deep-neural-network-what-is-it-and-how-is-it-working","title":{"rendered":"Deep Neural Network: What is it and how is it working?"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"166192\" class=\"elementor elementor-166192\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-335d537 e-flex e-con-boxed e-con\" data-id=\"335d537\" 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-f1913c0 elementor-widget elementor-widget-text-editor\" data-id=\"f1913c0\" 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;\">The Deep Neural Network imitates the functioning of the human brain. Find out everything you need to know about it: definition, functioning, use cases, training.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">A neural network is a <\/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);\">set of algorithms<\/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);\"> inspired by the human brain. The goal of this technology is to simulate the activity of the human brain, and more specifically the recognition of patterns and the transmission of information between the different layers of neural connections.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">A Deep Neural Network has <\/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);\">one particularity<\/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);\">: it is composed of at least two layers. This allows it to process data in a complex way, using advanced mathematical models.<\/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-0096515 e-flex e-con-boxed e-con\" data-id=\"0096515\" 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-c1f5bf3 elementor-widget elementor-widget-heading\" data-id=\"c1f5bf3\" 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\">How does a Deep Neural Network work?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-934955d elementor-widget elementor-widget-text-editor\" data-id=\"934955d\" 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 general, a Deep Neural Network has an input layer, an output layer and at least one layer in between. The higher the number of layers, the deeper the network. Each of these layers performs different types of specific sorting and categorization in a process called &#8220;<\/span><b>feature hierarchy<\/b><span style=\"font-weight: 400;\">&#8220;.<\/span><\/p><p><span style=\"font-weight: 400;\">To better understand how a Deep Neural Network works, we only need to observe <\/span><b>how the human brain works<\/b><span style=\"font-weight: 400;\">. Rather than learning the structure of the face to identify people, our brains learn from the deviation of a basic face that serves as a model.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">When we see a face, the brain tries to determine how it differs from this reference model. Features such as eyes, ears or eyebrows are thus reviewed in a fraction of a second.<\/span><\/p><p><span style=\"font-weight: 400;\">The differences between the perceived face and the &#8220;baseline&#8221; face model are quantified by an electrical signal of <\/span><b>varying strength<\/b><span style=\"font-weight: 400;\">. All deviations are combined to produce a result.<\/span><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 individual nodes in the system are similar to neurons in the human brain. Each layer is composed of <\/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);\">several nodes<\/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);\">. As soon as they are touched by stimuli, a process is triggered.<\/span><\/p><p><span style=\"font-weight: 400;\">The neural network <\/span><b>interprets the data <\/b><span style=\"font-weight: 400;\">collected by sensors or directly injected by a programmer. This data can be images, texts or even sounds that will then be converted into numerical values.<\/span><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 different data between the input layer and the output layer must be processed progressively to solve a task or make a prediction. 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);\">first layer <\/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);\">of the network receives the data and performs an activation function calculation to produce a result. This may be a <\/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);\">probability prediction<\/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);\">, for example.<\/span><\/p><p><span style=\"font-weight: 400;\">This result is transmitted to the <\/span><b>next layer of neurons<\/b><span style=\"font-weight: 400;\">. The connection between two successive layers is associated with a &#8220;weight&#8221;. This weight defines the influence of the data on the result produced by the next layer and eventually on the final result.<\/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-0e91fc9 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"0e91fc9\" 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\/deep-learning-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\">Everything about Deep Neural Network <\/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-ba4e14d elementor-widget elementor-widget-spacer\" data-id=\"ba4e14d\" 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-26dc4fb e-flex e-con-boxed e-con\" data-id=\"26dc4fb\" 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-f835eb8 elementor-widget elementor-widget-heading\" data-id=\"f835eb8\" 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: learning from deep neural networks<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5296051 elementor-widget elementor-widget-text-editor\" data-id=\"5296051\" 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 order to be able to imitate the functioning of the human brain to classify the data provided to it, a neural network must be trained beforehand. This is <\/span><strong><a href=\"https:\/\/datascientest.com\/en\/all-about-deep-learning\">Deep Learning<\/a><\/strong><span style=\"font-weight: 400;\">: a specific form of <\/span><a href=\"https:\/\/datascientest.com\/en\/machine-learning-what-is-it-and-why-does-it-change-the-world\"><span style=\"font-weight: 400;\"><strong>Machine Learning<\/strong><\/span><\/a><span style=\"font-weight: 400;\">.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">During the training phase, the AI is provided with example data. It learns to recognize patterns and features.<\/span><\/p><p><span style=\"font-weight: 400;\">When it receives new, unlabeled data, the artificial neural network tries to <\/span><b>categorize<\/b><span style=\"font-weight: 400;\"> it. Its prediction may be correct or incorrect, and it is up to the programmer to correct it if it is wrong. As the <\/span><b>system learns<\/b><span style=\"font-weight: 400;\"> from its mistakes, its success rate improves until its predictions become infallible.<\/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-f2b29b2 elementor-widget elementor-widget-spacer\" data-id=\"f2b29b2\" 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-fc56b9c e-flex e-con-boxed e-con\" data-id=\"fc56b9c\" 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-3df0acc elementor-widget elementor-widget-heading\" data-id=\"3df0acc\" 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 a Deep Neural Network used for?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-00afcf8 elementor-widget elementor-widget-text-editor\" data-id=\"00afcf8\" 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;\">One of the main use cases of these advanced neural networks is the processing of unstructured data. Deep neural networks can cluster and classify data stored in a database. This is very useful for organizing data without labels or structure.<\/span><\/p><p><span style=\"font-weight: 400;\">A deep neural network is very useful to <\/span><b>automate some human work<\/b><span style=\"font-weight: 400;\"> tasks. It is used in the field of video surveillance for facial recognition technology. Autonomous cars also depend on this technology.<\/span><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 same goes for virtual assistants like Siri and Alexa, or even the recommendation engines on Netflix, Spotify or Amazon. So without even knowing it, you probably use products based on<\/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);\"> deep neural networks<\/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);\"> on a daily basis.<\/span><\/p><p><span style=\"font-weight: 400;\">Moreover, <\/span><b>Deep Learning<\/b><span style=\"font-weight: 400;\"> is making its way into every industry. It is being used in the health field to detect cancer or retinopathy. In the aviation field, it is used to optimize airline fleets.<\/span><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);\">oil and gas industry<\/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 turning to deep artificial neural networks for predictive maintenance of machines. Banks and financial services, for their part, are adopting it for fraud detection. Little by little, Deep Learning is transforming all sectors of activity.<\/span><\/p><p><span style=\"font-weight: 400;\">Deep Neural Networks are the last link in the evolution of artificial intelligence. Originally, Machine Learning was used to <\/span><b>automate statistical models<\/b><span style=\"font-weight: 400;\"> through algorithms to make better predictions.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">A Machine Learning model is able to <\/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);\">make predictions<\/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);\"> for a single task. It simply learns by modifying its weights with each erroneous prediction to gain accuracy.<\/span><\/p><p><span style=\"font-weight: 400;\">Subsequently, artificial neural networks have emerged. These networks use a <\/span><b>hidden layer<\/b><span style=\"font-weight: 400;\"> to store and evaluate the impact of each input on the final output. Information about the impact of each input is stored and hidden, as well as associations between the data.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">Finally, deep neural networks have been invented. Rather than being satisfied with a single hidden layer, Deep Neural Networks <\/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);\">go even further<\/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);\"> by combining multiple hidden layers for even more benefits.<\/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-4a1e0ce elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"4a1e0ce\" 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\/deep-learning-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\">Follow a Deep Learning course<\/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-e120e55 elementor-widget elementor-widget-spacer\" data-id=\"e120e55\" 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-8c05ca7 e-flex e-con-boxed e-con\" data-id=\"8c05ca7\" 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-5eeffb2 elementor-widget elementor-widget-heading\" data-id=\"5eeffb2\" 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 are the Deep Learning frameworks?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-89c2b6b elementor-widget elementor-widget-text-editor\" data-id=\"89c2b6b\" 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 Deep Learning frameworks dedicated to training Deep Neural Networks. Several large companies and startups have launched <\/span><b>open source projects<\/b><span style=\"font-weight: 400;\"> to facilitate the training of Deep Neural Networks.<\/span><\/p><p><span style=\"font-weight: 400;\">These tools deliver reusable code blocks, allowing the abstraction of Deep Learning logic blocks. They also offer very useful modules for model development.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">Among the <strong>most popular Deep Learning frameworks<\/strong>, we can mention the <\/span><strong style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\"><a href=\"https:\/\/datascientest.com\/en\/tensor-flow-all-about-googles-machine-learning-framework\">open source project TensorFlow<\/a><\/strong><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\"> from Google, MxNet or the PyTorch library for Python created by Facebook. There are other, more advanced frameworks, like Keras based on TensorFlow or <strong>Gluon<\/strong> based on MxNet.<\/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-788f7fe elementor-widget__width-initial elementor-widget elementor-widget-video\" data-id=\"788f7fe\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=KNAWp2S3w94&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.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-video .elementor-widget-container{overflow:hidden;transform:translateZ(0)}.elementor-widget-video .elementor-wrapper{aspect-ratio:var(--video-aspect-ratio)}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{height:100%;width:100%;display:flex;border:none;background-color:#000}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-wrapper{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .elementor-open-inline .elementor-custom-embed-image-overlay{position:absolute;top:0;right:0;bottom:0;left:0;background-size:cover;background-position:50%}.elementor-widget-video .elementor-custom-embed-image-overlay{cursor:pointer;text-align:center}.elementor-widget-video .elementor-custom-embed-image-overlay:hover .elementor-custom-embed-play i{opacity:1}.elementor-widget-video .elementor-custom-embed-image-overlay img{display:block;width:100%;aspect-ratio:var(--video-aspect-ratio);-o-object-fit:cover;object-fit:cover;-o-object-position:center center;object-position:center center}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-custom-embed-image-overlay{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-custom-embed-image-overlay img{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .e-hosted-video .elementor-video{-o-object-fit:cover;object-fit:cover}.e-con-inner>.elementor-widget-video,.e-con>.elementor-widget-video{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\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-456de9e elementor-widget elementor-widget-spacer\" data-id=\"456de9e\" 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-3064f48 e-flex e-con-boxed e-con\" data-id=\"3064f48\" 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-b66c656 elementor-widget elementor-widget-heading\" data-id=\"b66c656\" 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\">How to learn to work with Deep Neural Networks?\n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a8185d6 elementor-widget elementor-widget-text-editor\" data-id=\"a8185d6\" 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 Neural Networks and Deep Learning offer <\/span><b>many opportunities<\/b><span style=\"font-weight: 400;\"> for companies in all industries. However, it is a complex technology that requires advanced knowledge and skills.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">To learn how to create and use such deep neural networks, you can turn to <\/span><strong style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\"><a href=\"https:\/\/datascientest.com\/en\/data-scientist-course\">DataScientest&#8217;s Data Scientist training<\/a><\/strong><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">. This program allows you to learn all aspects of being a data scientist.<\/span><\/p><p><span style=\"font-weight: 400;\">In the &#8220;<\/span><strong><a href=\"https:\/\/datascientest.com\/en\/deep-learning-course\">Deep Learning&#8221; module<\/a><\/strong><span style=\"font-weight: 400;\">, you will learn about the <\/span><strong><a href=\"https:\/\/datascientest.com\/en\/tensor-flow-all-about-googles-machine-learning-framework\">TensorFlow<\/a><\/strong><span style=\"font-weight: 400;\"> and <\/span><b>Keras<\/b><span style=\"font-weight: 400;\"> frameworks. You will learn all about the different types of neural networks such as CNNs, RNNs and GANs (generative adversarial networks).<\/span><\/p><p><span style=\"font-weight: 400;\">At the end of this course, you will have all the skills required to become a Data Scientist and will receive a degree certified by <\/span><b>the Sorbonne University<\/b><span style=\"font-weight: 400;\">. Among our alumni, 90% have found a job immediately after the training.<\/span><span style=\"color: var( --e-global-color-text ); font-family: var( --e-global-typography-text-font-family ), Sans-serif; text-align: var(--text-align);\">All of our courses adopt an innovative <\/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);\">Blended Learning approach<\/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);\">, combining classroom and distance learning. It is possible to achieve this learning in 6 months in Continuing Education, or in 9 weeks in BootCamp. Don&#8217;t wait any longer and discover 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);\">Data Scientist training.<\/b><\/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-03fd306 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"03fd306\" 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\/deep-learning-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\">Learn mode about Deep Neural Networks<\/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-c3dad2d elementor-widget elementor-widget-spacer\" data-id=\"c3dad2d\" 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-1e090fe e-flex e-con-boxed e-con\" data-id=\"1e090fe\" 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-9a4e00a elementor-widget elementor-widget-html\" data-id=\"9a4e00a\" 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\": \"How does a Deep Neural Network work?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"In general, a Deep Neural Network has an input layer, an output layer and at least one layer in between. 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The goal of this technology is to simulate the activity of the human brain, and more specifically the [&hellip;]<\/p>\n","protected":false},"author":63,"featured_media":85974,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2425],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Deep Neural Network: What is it and how is it working?<\/title>\n<meta name=\"description\" content=\"The Deep Neural Network imitates the functioning of the human brain. 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