{"id":53218,"date":"2024-04-15T23:50:48","date_gmt":"2024-04-15T23:50:48","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=53218"},"modified":"2024-04-15T23:50:48","modified_gmt":"2024-04-15T23:50:48","slug":"what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/","title":{"rendered":"What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value 2. Reiterate until you find the best weights of network 3. Pass an input through the network and get values from output layer 4. Initialize random weight and bias 5. Go to each neurons which contributes to the error and change its respective values to reduce the error"},"content":{"rendered":"<p>\r\n    <!-- Check if it's an AMP page -->\r\n            <!-- Non-AMP version -->\r\n        <div class=\"mcq-container\" data-quiz-id=\"quizState_6a985fb7ad697\">\r\n                                            <div class=\"option\" data-option-key=\"option1\" data-is-correct=\"true\">\r\n                    1, 2, 3, 4, 5                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option2\" data-is-correct=\"false\">\r\n                    4, 3, 1, 5, 2                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option3\" data-is-correct=\"false\">\r\n                    3, 2, 1, 5, 4                <\/div>\r\n                                            <div class=\"option\" data-option-key=\"option4\" data-is-correct=\"false\">\r\n                    5, 4, 3, 2, 1                <\/div>\r\n                            \r\n            <!-- Feedback messages for non-AMP -->\r\n            <div class=\"feedback\" data-feedback=\"wrong\">Answer is Right!<\/div>\r\n            <div class=\"feedback\" data-feedback=\"right\">Answer is Wrong!<\/div>\r\n        <\/div>\r\n\r\n        <script>\r\n        document.addEventListener('DOMContentLoaded', function () {\r\n            var containers = document.querySelectorAll('.mcq-container');\r\n\r\n            containers.forEach(function(container) {\r\n                var options = container.querySelectorAll('.option');\r\n                var feedbackSelect = container.querySelector('[data-feedback=\"select\"]');\r\n                var feedbackWrong = container.querySelector('[data-feedback=\"wrong\"]');\r\n                var feedbackRight = container.querySelector('[data-feedback=\"right\"]');\r\n\r\n                options.forEach(function(option) {\r\n                    option.addEventListener('click', function() {\r\n                        var selectedOption = option.getAttribute('data-option-key');\r\n                        var isCorrect = option.getAttribute('data-is-correct') === 'true';\r\n\r\n                        \/\/ Remove previous selections\r\n                        options.forEach(function(opt) {\r\n                            opt.classList.remove('correct', 'incorrect');\r\n                        });\r\n\r\n                        \/\/ Add the correct\/incorrect class\r\n                        if (isCorrect) {\r\n                            option.classList.add('correct');\r\n                            feedbackRight.hidden = false;\r\n                            feedbackWrong.hidden = true;\r\n                        } else {\r\n                            option.classList.add('incorrect');\r\n                            feedbackRight.hidden = true;\r\n                            feedbackWrong.hidden = false;\r\n                        }\r\n\r\n                        \/\/ Hide select feedback\r\n                        feedbackSelect.hidden = true;\r\n                    });\r\n                });\r\n            });\r\n        });\r\n        <\/script>\r\n    \r\n    <!--more--><\/p>\n<p>The correct answer is: A. 1, 2, 3, 4, 5<\/p>\n<p>Gradient descent is an iterative optimization algorithm for finding the minimum of a function. It is used in machine learning to train neural networks. The steps involved in gradient descent are as follows:<\/p>\n<ol>\n<li>Initialize the weights and biases of the network randomly.<\/li>\n<li>Pass an input through the network and get values from the output layer.<\/li>\n<li>Calculate the error between the actual value and the predicted value.<\/li>\n<li>Go to each neuron which contributes to the error and change its respective values to reduce the error.<\/li>\n<li>Repeat steps 2-4 until the error is minimized.<\/li>\n<\/ol>\n<p>The following is a brief explanation of each step:<\/p>\n<ol>\n<li>Initialize the weights and biases of the network randomly. This is done to ensure that the network starts from a random point in the search space.<\/li>\n<li>Pass an <div class=\"youtube-subscribe-container\">\r\n        <a href=\"https:\/\/www.youtube.com\/channel\/UCNHT8lW-JmLC68rjBfZhdkg?sub_confirmation=1\" target=\"_blank\" class=\"youtube-subscribe-button\">\r\n            <span class=\"youtube-icon\">\r\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 576 512\">\r\n                    <path d=\"M549.7 124.1c-6.3-23.7-24.8-42.3-48.3-48.6C458.8 64 288 64 288 64S117.2 64 74.6 75.5c-23.5 6.3-42 24.9-48.3 48.6-11.4 42.9-11.4 132.3-11.4 132.3s0 89.4 11.4 132.3c6.3 23.7 24.8 41.5 48.3 47.8C117.2 448 288 448 288 448s170.8 0 213.4-11.5c23.5-6.3 42-24.2 48.3-47.8 11.4-42.9 11.4-132.3 11.4-132.3s0-89.4-11.4-132.3zm-317.5 213.5V175.2l142.7 81.2-142.7 81.2z\"\/>\r\n  <div class=\"telegram-channel-container\">\r\n        <a href=\"https:\/\/t.me\/pscnotes2025\" target=\"_blank\" class=\"telegram-channel-button\">\r\n            <span class=\"telegram-icon\">\r\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 496 512\">\r\n                    <path fill=\"white\" d=\"M248,8C111,8,0,119,0,256s111,248,248,248s248-111,248-248S385,8,248,8z M362,177L320,367c-3,14-10,18-20,14l-56-41l-27,26 c-3,3-5,5-10,5l4-63L323,196c5-5-1-7-8-3l-98,62l-42-13c-9-3-10-9,2-14l162-63C351,160,365,164,362,177z\"\/>\r\n                <\/svg>\r\n            <\/span>\r\n            Join Our Telegram Channel\r\n        <\/a>\r\n    <\/div>               <\/svg>\r\n            <\/span>\r\n            Subscribe on YouTube\r\n        <\/a>\r\n    <\/div> input through the network and get values from the output layer. This is done to calculate the error between the actual value and the predicted value.<\/li>\n<li>Calculate the error between the actual value and the predicted value. This is done to determine how much the network needs to be updated.<\/li>\n<li>Go to each neuron which contributes to the error and change its respective values to reduce the error. This is done by updating the weights and biases of the network.<\/li>\n<li>Repeat steps 2-4 until the error is minimized. This is done until the network converges to a minimum value for the error.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Join Our Telegram Channel Subscribe on YouTube<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[729],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.2 (Yoast SEO v23.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value 2. Reiterate until you find the best weights of network 3. Pass an input through the network and get values from output layer 4. Initialize random weight and bias 5. Go to each neurons which contributes to the error and change its respective values to reduce the error<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value 2. Reiterate until you find the best weights of network 3. Pass an input through the network and get values from output layer 4. Initialize random weight and bias 5. Go to each neurons which contributes to the error and change its respective values to reduce the error\" \/>\n<meta property=\"og:description\" content=\"Subscribe on YouTube\" \/>\n<meta property=\"og:url\" content=\"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/\" \/>\n<meta property=\"og:site_name\" content=\"MCQ and Quiz for Exams\" \/>\n<meta property=\"article:published_time\" content=\"2024-04-15T23:50:48+00:00\" \/>\n<meta name=\"author\" content=\"rawan239\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"rawan239\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value 2. Reiterate until you find the best weights of network 3. Pass an input through the network and get values from output layer 4. Initialize random weight and bias 5. Go to each neurons which contributes to the error and change its respective values to reduce the error","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/","og_locale":"en_US","og_type":"article","og_title":"What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value 2. Reiterate until you find the best weights of network 3. Pass an input through the network and get values from output layer 4. Initialize random weight and bias 5. Go to each neurons which contributes to the error and change its respective values to reduce the error","og_description":"Subscribe on YouTube","og_url":"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/","og_site_name":"MCQ and Quiz for Exams","article_published_time":"2024-04-15T23:50:48+00:00","author":"rawan239","twitter_card":"summary_large_image","twitter_misc":{"Written by":"rawan239","Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/","url":"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/","name":"What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value 2. Reiterate until you find the best weights of network 3. Pass an input through the network and get values from output layer 4. Initialize random weight and bias 5. Go to each neurons which contributes to the error and change its respective values to reduce the error","isPartOf":{"@id":"https:\/\/exam.pscnotes.com\/mcq\/#website"},"datePublished":"2024-04-15T23:50:48+00:00","dateModified":"2024-04-15T23:50:48+00:00","author":{"@id":"https:\/\/exam.pscnotes.com\/mcq\/#\/schema\/person\/5807dafeb27d2ec82344d6cbd6c3d209"},"breadcrumb":{"@id":"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/exam.pscnotes.com\/mcq\/what-are-the-steps-for-using-a-gradient-descent-algorithm-1-calculate-error-between-the-actual-value-and-the-predicted-value-2-reiterate-until-you-find-the-best-weights-of-network-3-pass-an-input\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/exam.pscnotes.com\/mcq\/"},{"@type":"ListItem","position":2,"name":"mcq","item":"https:\/\/exam.pscnotes.com\/mcq\/category\/mcq\/"},{"@type":"ListItem","position":3,"name":"Machine learning","item":"https:\/\/exam.pscnotes.com\/mcq\/category\/mcq\/machine-learning\/"},{"@type":"ListItem","position":4,"name":"What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value 2. Reiterate until you find the best weights of network 3. Pass an input through the network and get values from output layer 4. Initialize random weight and bias 5. Go to each neurons which contributes to the error and change its respective values to reduce the error"}]},{"@type":"WebSite","@id":"https:\/\/exam.pscnotes.com\/mcq\/#website","url":"https:\/\/exam.pscnotes.com\/mcq\/","name":"MCQ and Quiz for Exams","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/exam.pscnotes.com\/mcq\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/exam.pscnotes.com\/mcq\/#\/schema\/person\/5807dafeb27d2ec82344d6cbd6c3d209","name":"rawan239","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/exam.pscnotes.com\/mcq\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/d97f17072bfa490596c8f78363955d55?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/d97f17072bfa490596c8f78363955d55?s=96&d=mm&r=g","caption":"rawan239"},"sameAs":["https:\/\/exam.pscnotes.com"],"url":"https:\/\/exam.pscnotes.com\/mcq\/author\/rawan239\/"}]}},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/posts\/53218"}],"collection":[{"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/comments?post=53218"}],"version-history":[{"count":0,"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/posts\/53218\/revisions"}],"wp:attachment":[{"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/media?parent=53218"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/categories?post=53218"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/exam.pscnotes.com\/mcq\/wp-json\/wp\/v2\/tags?post=53218"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}