{"id":165450,"date":"2023-06-02T15:07:11","date_gmt":"2023-06-02T14:07:11","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=165450"},"modified":"2023-10-30T19:10:52","modified_gmt":"2023-10-30T18:10:52","slug":"epoch-an-essential-notion","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/epoch-an-essential-notion","title":{"rendered":"Epoch : An essential notion in real-time programming"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"165450\" class=\"elementor elementor-165450\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c16b519 e-flex e-con-boxed e-con\" data-id=\"c16b519\" 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-28411b8 elementor-widget elementor-widget-heading\" data-id=\"28411b8\" 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><h2 class=\"elementor-heading-title elementor-size-default\"><span><p dir=\"ltr\" style=\"line-height:1.38;margin-top:0pt;margin-bottom:0pt;\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">An epoch in Machine Learning refers to one complete pass of the training data set through the algorithm. Learn all you need to know about this essential concept of machine learning.<\/span><\/p><p dir=\"ltr\" style=\"line-height:1.38;margin-top:0pt;margin-bottom:0pt;\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">In the field of artificial intelligence, Machine Learning involves allowing a model to learn and train from data using an algorithm. This method is inspired by the way the human brain learns, and is based on artificial neural networks.<\/span><span style=\"color: var( --e-global-color-primary ); font-family: var( --e-global-typography-primary-font-family ), Sans-serif; font-weight: var( --e-global-typography-primary-font-weight ); text-align: var(--text-align);\"><\/span><\/p><\/span><\/h2>\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-e096dfc e-flex e-con-boxed e-con\" data-id=\"e096dfc\" 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-ef14d9e elementor-widget elementor-widget-text-editor\" data-id=\"ef14d9e\" 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;\">However, while a human needs several years to learn, through techniques such as parallel training, a model can train for the equivalent of several decades in just a few hours.<\/span><\/p><p><span style=\"font-weight: 400;\">Furthermore, each time the training dataset passes through the algorithm, it is said to have <\/span><b>completed an epoch<\/b><span style=\"font-weight: 400;\">. This is a hyperparameter, determining the training process of the <\/span><a href=\"https:\/\/datascientest.com\/en\/machine-learning-what-is-it-and-why-does-it-change-the-world\"><b><u>Machine Learning<\/u><\/b><\/a><span style=\"font-weight: 400;\"> model.<\/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-6155390 e-flex e-con-boxed e-con\" data-id=\"6155390\" 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-f12ef0b elementor-widget elementor-widget-heading\" data-id=\"f12ef0b\" 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\"><span style=\"font-weight:normal;\" id=\"docs-internal-guid-338e8a8b-7fff-fdb5-570d-d7b5bf1ae837\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">What is an Epoch?<\/span><\/span><\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-aa0a3c5 elementor-widget elementor-widget-text-editor\" data-id=\"aa0a3c5\" 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 complete pass of the training dataset is considered an &#8220;epoch&#8221; in the field of Machine Learning. It reflects the <\/span><b>number of passes<\/b><span style=\"font-weight: 400;\"> of the algorithm during the training phase.<\/span><\/p><p><span style=\"font-weight: 400;\">An epoch can be defined as the number of passes of a <\/span><b>training dataset <\/b><span style=\"font-weight: 400;\">through an algorithm. One pass is equivalent to a round trip. The number of epochs can reach several thousand, as the procedure is repeated indefinitely until the model&#8217;s error rate is reduced to an acceptable level.<\/span><\/p><p><span style=\"font-weight: 400;\">An epoch is made up of an aggregation of <\/span><b>&#8220;batches&#8221;<\/b><span style=\"font-weight: 400;\"> of data and iterations. Data sets are generally broken down into batches, particularly when the volume of data is massive.<\/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-2515b2f elementor-widget elementor-widget-image\" data-id=\"2515b2f\" 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\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/epoch-machine-learning-1.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e9a91a9 e-flex e-con-boxed e-con\" data-id=\"e9a91a9\" 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-2f915b9 elementor-widget elementor-widget-heading\" data-id=\"2f915b9\" 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\"><span style=\"font-weight:normal;\" id=\"docs-internal-guid-c5ad6725-7fff-1c16-e17d-69a1cbf3aa7d\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">What is an iteration?<\/span><\/span><\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ffdfc87 elementor-widget elementor-widget-text-editor\" data-id=\"ffdfc87\" 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 Machine Learning field, an iteration indicates <\/span><b>the number of times that the parameters of an algorithm are modified<\/b><span style=\"font-weight: 400;\">. The specific implications depend on the context.<\/span><\/p><p><span style=\"font-weight: 400;\">Generally, a training iteration of a neural network includes batch processing or processing of the dataset in batches, <\/span><b>calculation of the cost function<\/b><span style=\"font-weight: 400;\">, modification and backpropagation of all weight factors.<\/span><\/p><p><span style=\"font-weight: 400;\">Iteration and epoch are often wrongly confused. In reality, an iteration involves the processing of a batch while an epoch refers to the processing of all the data in the dataset.<\/span><\/p><p><span style=\"font-weight: 400;\">For example, if an iteration processes 10 images of a set of 1000 images with a batch size of 10, it will take 100 iterations to complete one epoch.<\/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-5229b9c e-flex e-con-boxed e-con\" data-id=\"5229b9c\" 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-692fb2e elementor-widget elementor-widget-heading\" data-id=\"692fb2e\" 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\"><span style=\"font-weight:normal;\" id=\"docs-internal-guid-be3704d3-7fff-3218-4ec4-a37c2d8c71f3\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">What is a batch?<\/span><\/span><\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ef3ce1a elementor-widget elementor-widget-text-editor\" data-id=\"ef3ce1a\" 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;\">Training data is broken down into several small &#8220;batches.&#8221; The goal is to avoid problems related to <\/span><b>lack of storage space<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Batches can be easily used to feed the Machine Learning model in order to train it. This process of breaking down the dataset is called &#8220;<\/span><b>batch processing<\/b><span style=\"font-weight: 400;\">&#8220;.<\/span><\/p><p><span style=\"font-weight: 400;\">One epoch can be made up of one batch or more. The number of training samples used in one iteration is the &#8220;batch size\u201d. There are three possibilities :\u00a0<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">In &#8220;<\/span><b>batch mode<\/b><span style=\"font-weight: 400;\">,&#8221; the values of iteration and epoch are equal since the batch size is equal to the complete dataset. Therefore, <\/span><b>one iteration is equivalent to one epoch<\/b><span style=\"font-weight: 400;\">.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">In &#8220;<\/span><b>mini-batch mode<\/b><span style=\"font-weight: 400;\">&#8220;, the size of the complete dataset is smaller than the batch size. Therefore, a single batch is larger than the training dataset.<\/span><\/li><\/ul><p dir=\"ltr\">\u00a0<\/p><p dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;\"><span style=\"font-weight: 400;\">Finally, in &#8220;<\/span><b>stochastic mode<\/b><span style=\"font-weight: 400;\">&#8220;, the batch size is unique. Therefore, the gradient and parameters of the neural network are <\/span><b>changed with each sample<\/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-84c1963 elementor-widget elementor-widget-image\" data-id=\"84c1963\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/epoch-machine-learning-2.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-b2b346b e-flex e-con-boxed e-con\" data-id=\"b2b346b\" 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-abb25b6 elementor-widget elementor-widget-heading\" data-id=\"abb25b6\" 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\"><span style=\"font-weight:normal;\" id=\"docs-internal-guid-8b2ba9b9-7fff-534a-98cf-6b3d3dfd5c38\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">What is the stochastic gradient descent algorithm?<\/span><\/span><\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1ed9f80 elementor-widget elementor-widget-text-editor\" data-id=\"1ed9f80\" 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>Stochastic Gradient Descent<\/b><span style=\"font-weight: 400;\"> (SGD) algorithm is an optimization algorithm. It is used by neural networks in the field of <\/span><a href=\"https:\/\/datascientest.com\/en\/all-about-deep-learning\"><u><b>Deep Learning<\/b><\/u> <\/a><span style=\"font-weight: 400;\">to train Machine Learning algorithms.<\/span><\/p><p><span style=\"font-weight: 400;\">The role of this algorithm is to <\/span><b>identify a set of internal model parameters<\/b><span style=\"font-weight: 400;\"> that exceed other performance measures such as the mean squared error or log loss.<\/span><\/p><p><span style=\"font-weight: 400;\">Optimization can be described as a <\/span><b>search process involving learning<\/b><span style=\"font-weight: 400;\">. The optimization algorithm is called gradient descent, and it is based on the calculation of an error gradient or error slope that needs to be descended in the direction of the minimum error level.<\/span><\/p><p><span style=\"font-weight: 400;\">This algorithm allows the search process to be run multiple times. The aim is to improve the model&#8217;s parameters at each step. Therefore, it is an iterative algorithm.<\/span><\/p><p><span style=\"font-weight: 400;\">At each step, predictions are made using specific samples using the set of internal parameters. The predictions are then <\/span><b>compared to the expected results<\/b><span style=\"font-weight: 400;\"> to calculate the error rate. The internal parameters are then updated.<\/span><\/p><p><span style=\"font-weight: 400;\">Different algorithms use different update procedures. In the case of artificial neural networks, the algorithm uses the <\/span><b>backpropagation method<\/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\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-805550d e-flex e-con-boxed e-con\" data-id=\"805550d\" 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-8d63572 elementor-widget elementor-widget-heading\" data-id=\"8d63572\" 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\"><span style=\"font-weight:normal;\" id=\"docs-internal-guid-b37d9422-7fff-6c35-e939-e8dbc5d628a0\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">Batch size vs epoch: what's the difference?<\/span><\/span><\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-aa81d94 elementor-widget elementor-widget-text-editor\" data-id=\"aa81d94\" 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>batch size<\/b><span style=\"font-weight: 400;\"> is the number of samples processed before the model changes. The number of epochs is the number of complete iterations of the training dataset.<\/span><\/p><p><b>A batch must have a minimum size<\/b><span style=\"font-weight: 400;\"> of one and a maximum size that is less than or equal to the number of samples in the training dataset.<\/span><\/p><p><span style=\"font-weight: 400;\">For the number of epochs, it is possible to choose an integer value between one and infinity. The processing can be run indefinitely and even be stopped by criteria other than a predetermined number of epochs. For example, the criterion may be the model&#8217;s error rate.<\/span><\/p><p><span style=\"font-weight: 400;\">The batch size and number of epochs are <\/span><b>hyperparameters of the learning algorithm<\/b><span style=\"font-weight: 400;\"> and must be indicated to the algorithm. These parameters must be configured by testing many values to determine which is optimal.<\/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-e292c17 elementor-widget elementor-widget-image\" data-id=\"e292c17\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/batch-vs-epoch.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-56e003c e-flex e-con-boxed e-con\" data-id=\"56e003c\" 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-936a1db elementor-widget elementor-widget-heading\" data-id=\"936a1db\" 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\"><span style=\"font-weight:normal;\" id=\"docs-internal-guid-c3c0cc16-7fff-89da-52fc-8a38f89afe5d\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">How to choose the number of epochs?<\/span><\/span><\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7843217 elementor-widget elementor-widget-text-editor\" data-id=\"7843217\" 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;\">After each iteration of the neural network, the <strong>weights are modified<\/strong>. The curve evolves from underfitting to overfitting, passing through the ideal fit. The number of epochs is a hyperparameter that must be decided before training begins.<\/span><\/p><p><span style=\"font-weight: 400;\">A larger number of epochs does not necessarily lead to better results. Generally, a number of 11 epochs is ideal for training on most datasets.<\/span><\/p><p><span style=\"font-weight: 400;\">Learning optimization is <\/span><b>based on the iterative process of gradient descent<\/b><span style=\"font-weight: 400;\">. This is why a single epoch is not enough to optimally modify the weights. On the contrary, an extra epoch can cause the model to overfit&#8230;<\/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-04b63e4 e-flex e-con-boxed e-con\" data-id=\"04b63e4\" 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-81b86db elementor-widget elementor-widget-heading\" data-id=\"81b86db\" 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\"><span style=\"font-weight:normal;\" id=\"docs-internal-guid-50b23e9e-7fff-a14e-7bd9-841911b82eff\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">Why is epoch essential in Machine Learning?<\/span><\/span><\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3725bb6 elementor-widget elementor-widget-text-editor\" data-id=\"3725bb6\" 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 epoch is <\/span><b>one of the crucial concepts in Machine Learning<\/b><span style=\"font-weight: 400;\">. It helps to identify the model that represents the data as faithfully as possible.<\/span><\/p><p><span style=\"font-weight: 400;\">The neural network must be trained based on the number of epochs and batch size indicated to the algorithm. This hyperparameter therefore <\/span><b>determines the entire course<\/b><span style=\"font-weight: 400;\"> of the process.<\/span><\/p><p><span style=\"font-weight: 400;\">In any case, there is no secret recipe or magic formula for defining the ideal value of each parameter. Data analysts have no choice but to <\/span><b>test a wide variety of values<\/b><span style=\"font-weight: 400;\"> before choosing the one that is best suited to solving the specific problem.<\/span><\/p><p><span style=\"font-weight: 400;\">One method for determining the appropriate number of epochs is to monitor learning performance by comparing this number with the model&#8217;s error rate. The learning curve is very useful for checking whether a model is overfitting, underfitting, or adequately trained.<\/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-9efb7c1 e-flex e-con-boxed e-con\" data-id=\"9efb7c1\" 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<div class=\"elementor-element elementor-element-671817a e-flex e-con-boxed e-con\" data-id=\"671817a\" 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<div class=\"elementor-element elementor-element-7ba03fc e-con-full e-flex e-con\" data-id=\"7ba03fc\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-320f045 elementor-widget elementor-widget-image\" data-id=\"320f045\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/machine-learning-4.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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>\n\t\t<div class=\"elementor-element elementor-element-b068cdf e-con-full e-flex e-con\" data-id=\"b068cdf\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4336cd8 elementor-widget elementor-widget-image\" data-id=\"4336cd8\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/machine-learning-2.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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>\n\t\t<div class=\"elementor-element elementor-element-d168444 e-con-full e-flex e-con\" data-id=\"d168444\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;full&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5ae5079 elementor-widget elementor-widget-image\" data-id=\"5ae5079\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/machine-learning-3.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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>\n\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-a663991 e-flex e-con-boxed e-con\" data-id=\"a663991\" 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-cc55e2e elementor-widget elementor-widget-heading\" data-id=\"cc55e2e\" 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\"><span style=\"font-weight:normal;\" id=\"docs-internal-guid-aa5de75b-7fff-bd19-7b53-74985f106e9e\"><span style=\"font-size: 15pt; font-family: Arial; background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; vertical-align: baseline;\">How to follow a Machine Learning course?<\/span><\/span><\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-764cd43 elementor-widget elementor-widget-text-editor\" data-id=\"764cd43\" 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, the epoch is a term used to describe the frequency at which training <\/span><b>data passes through the algorithm<\/b><span style=\"font-weight: 400;\">. It is one of the essential concepts of Machine Learning.<\/span><\/p><p><span style=\"font-weight: 400;\">To acquire expertise in this field, you can choose <\/span><b>DataScientest<\/b><span style=\"font-weight: 400;\">. Our <\/span><a href=\"https:\/\/datascientest.com\/en\/data-scientist-course\"><u><b>Data Scientist<\/b><\/u><\/a><span style=\"font-weight: 400;\">, <\/span><a href=\"https:\/\/datascientest.com\/en\/data-analyst-course\"><b><u>Data Analyst<\/u><\/b><\/a><span style=\"font-weight: 400;\">, and <\/span><a href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-course\"><b><u>Machine Learning Engineer<\/u><\/b><\/a><span style=\"font-weight: 400;\"> courses all include a module dedicated to Machine Learning.<\/span><\/p><p><span style=\"font-weight: 400;\">You will discover supervised and unsupervised learning, classification techniques, regression, clustering with scikit-learn, or even Text Mining, time series, and dimensionality reduction.<\/span><\/p><p><span style=\"font-weight: 400;\">Through the other modules of these curricula, you can acquire all the skills required to become a professional in <\/span><b>Data Science<\/b><span style=\"font-weight: 400;\">. You can pursue careers as a Data Analyst, Data Scientist, or Machine Learning Engineer depending on the chosen path.<\/span><\/p><p><span style=\"font-weight: 400;\">All our courses are fully conducted online via the internet and can be completed as Continuing Education or in a BootCamp. Our innovative <\/span><b>Blended Learning approach <\/b><span style=\"font-weight: 400;\">combines distance learning on a coached platform and Masterclass.<\/span><\/p><p><span style=\"font-weight: 400;\">At the end of the course, learners receive a certificate from Mines ParisTech PSL Executive Education and validate block 3 of the RNCP 36129 &#8220;<\/span><b>AI Project Manager&#8221; certification <\/b><span style=\"font-weight: 400;\">recognized by the French state. You can also take exams to obtain Microsoft Certified Power Platform Fundamentals or AWS Cloud Practitioner certifications.<\/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-4429b46 e-flex e-con-boxed e-con\" data-id=\"4429b46\" 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-91c945d elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"91c945d\" 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 our Data Science 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-d0436c5 e-flex e-con-boxed e-con\" data-id=\"d0436c5\" 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-26764b7 elementor-widget elementor-widget-text-editor\" data-id=\"26764b7\" 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;\">You know everything about the epoch in the field of Machine Learning. For more information on the same subject, discover our complete file on <\/span><a href=\"https:\/\/datascientest.com\/en\/tensor-flow-all-about-googles-machine-learning-framework\"><u><b>TensorFlow<\/b><\/u><\/a><span style=\"font-weight: 400;\">, a machine learning framework.<\/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-3d48a35 e-flex e-con-boxed e-con\" data-id=\"3d48a35\" 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-eef9f58 elementor-widget elementor-widget-html\" data-id=\"eef9f58\" 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 a batch?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Batches can be easily used to feed the Machine Learning model in order to train it. This process of breaking down the dataset is called \\\"batch processing\\\". One epoch can be made up of one batch or more. The number of training samples used in one iteration is the \\\"batch size\u201d.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Why is epoch essential in Machine Learning?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"The epoch is one of the crucial concepts in Machine Learning. It helps to identify the model that represents the data as faithfully as possible. The neural network must be trained based on the number of epochs and batch size indicated to the algorithm. This hyperparameter therefore determines the entire course of the process.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"How to choose the number of epochs?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"After each iteration of the neural network, the weights are modified. The curve evolves from underfitting to overfitting, passing through the ideal fit. The number of epochs is a hyperparameter that must be decided before training begins.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"What is the stochastic gradient descent algorithm?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"The Stochastic Gradient Descent (SGD) algorithm is an optimization algorithm. It is used by neural networks in the field of Deep Learning to train Machine Learning algorithms. The role of this algorithm is to identify a set of internal model parameters that exceed other performance measures such as the mean squared error or log loss.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"What is an Epoch?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"An epoch can be defined as the number of passes of a training dataset through an algorithm. One pass is equivalent to a round trip. The number of epochs can reach several thousand, as the procedure is repeated indefinitely until the model's error rate is reduced to an acceptable level.\"\r\n    }\r\n  }]\r\n}\r\n<\/script>\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\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>An epoch in Machine Learning refers to one complete pass of the training data set through the algorithm. Learn all you need to know about this essential concept of machine learning. In the field of artificial intelligence, Machine Learning involves allowing a model to learn and train from data using an algorithm. This method is [&hellip;]<\/p>\n","protected":false},"author":45,"featured_media":165825,"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>Epoch : An essential notion in real-time programming<\/title>\n<meta name=\"description\" content=\"In the field of artificial intelligence, Machine Learning involves allowing a model to learn and train from data using an algorithm. 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