{"id":95642,"date":"2022-09-23T21:47:30","date_gmt":"2022-09-23T19:47:30","guid":{"rendered":"https:\/\/rmarketingdigital.com\/javascript\/aprendizaje-automatico-con-javascript-parte-1\/"},"modified":"2020-12-05T11:30:17","modified_gmt":"2020-12-05T14:30:17","slug":"aprendizaje-automatico-con-javascript-parte-1","status":"publish","type":"post","link":"https:\/\/rmarketingdigital.com\/en\/javascript\/aprendizaje-automatico-con-javascript-parte-1\/","title":{"rendered":"Machine Learning with JavaScript: Part 1"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_86 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/rmarketingdigital.com\/en\/javascript\/aprendizaje-automatico-con-javascript-parte-1\/#Aprendizaje-Automatico-en-JS\" >Machine Learning in JS<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/rmarketingdigital.com\/en\/javascript\/aprendizaje-automatico-con-javascript-parte-1\/#%C2%BFPor-que-no-se-menciona-JavaScript-con-ML\" >Why is JavaScript not mentioned with ML?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/rmarketingdigital.com\/en\/javascript\/aprendizaje-automatico-con-javascript-parte-1\/#Paso-1-Instalar-las-bibliotecas\" >Step 1. Install the libraries<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/rmarketingdigital.com\/en\/javascript\/aprendizaje-automatico-con-javascript-parte-1\/#Datos-del-aposito-para-prepararlo-para-su-ejecucion\" >Dressing data to prepare it for execution<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/rmarketingdigital.com\/en\/javascript\/aprendizaje-automatico-con-javascript-parte-1\/#Entrena-a-tu-modelo-y-empieza-a-predecir\" >Train your model and start predicting<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/rmarketingdigital.com\/en\/javascript\/aprendizaje-automatico-con-javascript-parte-1\/#%C2%A1Ya-finalizamos\" >We are done!<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<div itemprop=\"articleBody\">\n<p>Today we will learn about Machine Learning in JS, and yes, if you&#039;re reading right.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Aprendizaje-Automatico-en-JS\"><\/span>Machine Learning in JS<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>JAVASCRIPT ?! Shouldn&#039;t you be using python? Am I crazy to test those calculations in JavaScript? Am I trying to act calm using a language other than python or R? <em>scikit-learn<\/em> doesn&#039;t even work in javascript?<\/p>\n<p>Short answer: No. I&#039;m not crazy.<\/p>\n<p>Long answer: It is possible and I am surprised that the developers did not give it the attention it deserves. Talking about <strong>scikit-learn,<\/strong> the folks at JS have created their own set of libraries to counter it, and I&#039;m going to use one too. But first, a little about machine learning.<\/p>\n<p>According to Arthur Samuel, machine learning gives computers the ability to learn without being explicitly programmed. In other words, it gives the computer the ability to teach itself and execute the correct instructions, without you giving it instructions.<\/p>\n<p>It&#039;s been around for quite some time, with Google moving from mobile-first to AI-first.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"%C2%BFPor-que-no-se-menciona-JavaScript-con-ML\"><\/span>Why is JavaScript not mentioned with ML?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>It is very slow. (This is a myth)<\/li>\n<li>Array manipulation is difficult (there are libraries, for example math.js).<\/li>\n<li>Just concerned with Web Development (Somewhere Node.js is laughing at this.)<\/li>\n<li>Libraries are usually made for python. (JS people are not behind)<\/li>\n<\/ul>\n<p>There are a handful of JavaScript libraries with algorithms for <strong>Machine learning<\/strong> pre-designed, such as <em>Linear Regression, SVMs, Naive-Bayes<\/em>, and so on. Here are some of them,<\/p>\n<ul>\n<li><strong>brain.js<\/strong> (Neural networks)<\/li>\n<li><strong>Synaptic<\/strong> (Neural networks)<\/li>\n<li><strong>natural<\/strong> (Natural language processing)<\/li>\n<li><strong>ConvNetJS<\/strong> (convolutional neural networks)<\/li>\n<li><strong>mljs<\/strong> (A set of sublibraries with a variety of functions)<\/li>\n<li><strong>Neat\u00e1ptic<\/strong> (Neural networks)<\/li>\n<li><strong>Webdnn<\/strong> (Deep Learning)<\/li>\n<\/ul>\n<p>We are going to use the regression library of <strong>mljs<\/strong> to perform some linear regression witchcraft hahaha.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Paso-1-Instalar-las-bibliotecas\"><\/span>Step 1. Install the libraries<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">$ yarn add ml-regression csvtojson\n<\/pre>\n<p>Or if you like <strong>npm<\/strong><\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">$ npm install ml-regression csvtojson\n<\/pre>\n<p><strong>ml-regression<\/strong> it does what the name implies.<\/p>\n<p><strong>csvtojson<\/strong> is a fast parser <strong>csv<\/strong> for <strong>node.js<\/strong> that allows uploading data files <strong>csv<\/strong> and convert them to <strong>JSON<\/strong>.<\/p>\n<p>Download the data file <em>(.csv)<\/em> since <a rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"http:\/\/www-bcf.usc.edu\/~gareth\/ISL\/Advertising.csv\">here<\/a> and put it inside your project.<\/p>\n<p>Assuming you have already initialized a project <strong>npm<\/strong> empty, open the file <strong>index.js<\/strong> and enter the following. (You can copy \/ paste if you want, but I prefer that you write it yourself for better understanding.)<\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">const ml = require (&#039;ml-regression&#039;); const csv = require (&#039;csvtojson&#039;); const SLR = ml.SLR; \/\/ Simple linear regression const csvFilePath = &#039;advertising.csv&#039;; \/\/ Data let csvData = [], \/\/ Parsed data X = [], \/\/ input y = []; \/\/ output let regressionModel;\n<\/pre>\n<p>Now we are going to use the method <strong>fromFile<\/strong> from <strong>csvtojson<\/strong> to load our data file.<\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">csv () .fromFile (csvFilePath) .on (&#039;json&#039;, (jsonObj) =&gt; {csvData.push (jsonObj);}) .on (&#039;done&#039;, () =&gt; {dressData (); \/\/ To get JSON object data points performRegression ();});\n<\/pre>\n<h3><span class=\"ez-toc-section\" id=\"Datos-del-aposito-para-prepararlo-para-su-ejecucion\"><\/span>Dressing data to prepare it for execution<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The objects <strong>JSON<\/strong> that we keep in <strong>csvData<\/strong> they are well, objects, and we need a series of input data points as well as output data points. We are going to execute our data through a function <strong>dressData<\/strong> which will fill in our variables X and y.<\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">function dressData () {\/ ** * A line in the data object looks like this: * {* TV: &quot;10&quot;, * Radio: &quot;100&quot;, * Newspaper: &quot;20&quot;, * &quot;Sales&quot;: &quot;1000 &quot;*} * * Therefore, when adding the data points, we need to parse the value * of the string as a float. * \/ csvData.forEach ((row) =&gt; {X.push (f (row.Radio)); y.push (f (row.Sales));}); } function f (s) {return parseFloat (s); }\n<\/pre>\n<h3><span class=\"ez-toc-section\" id=\"Entrena-a-tu-modelo-y-empieza-a-predecir\"><\/span>Train your model and start predicting<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Now that our data has been successfully dressed, it is time to train our model.<\/p>\n<p>To do this, we are going to write a function <strong>performRegression:<\/strong><\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">function performRegression () {regressionModel = new SLR (X, y); \/\/ Train the model on training data console.log (regressionModel.toString (3)); predictOutput (); }\n<\/pre>\n<p>The regression model has a method for <strong>String<\/strong> which takes a parameter called precision for floating point outputs.<\/p>\n<p>The function <strong>predictOutput<\/strong>\u00a0allows you to enter input values and sends the expected output to your console.<\/p>\n<p>This is what it looks like: (Note that I am using Node.js read line utility)<\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">function predictOutput () {rl.question (&#039;Enter input X for prediction (Press CTRL + C to exit):&#039;, (answer) =&gt; {console.log (`At X = $ {answer}, y = $ {regressionModel .predict (parseFloat (answer))} `); predictOutput ();}); }\n<\/pre>\n<p>And here is the code to add the user read input:<\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">const readline = require (&#039;readline&#039;); \/\/ For the user to ask for predictions to be allowed const rl = readline.createInterface ({input: process.stdin, output: process.stdout});\n<\/pre>\n<h3><span class=\"ez-toc-section\" id=\"%C2%A1Ya-finalizamos\"><\/span>We are done!<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>If you followed the steps, this is how your should look <strong>index.js:<\/strong><\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">const ml = require (&#039;regression ml-&#039;); const csv = require (&#039;csvtojson&#039;); const SLR = ml.SLR; \/\/ Simple linear regression const csvFilePath = &#039;advertising.csv&#039;; \/\/ Data let csvData = [], \/\/ Analyzed data X = [], \/\/ Input y = []; \/\/ Output let regressionModel; const readline = require (&#039;readline&#039;); \/\/ For the user to ask for predictions to be allowed const rl = readline.createInterface ({{) input: process.stdin, output: process.stdout}); csv () .fromFile (csvFilePath) .on (&#039;json&#039;, (jsonObj) =&gt; {csvData.push (jsonObj);}) .on (&#039;done&#039;, () =&gt; {dressData (); \/\/ To get JSON Objects data points performRegression ();}); function performRegression () {regressionModel = new SLR (X, y); \/\/ Train the model on training data console.log (regressionModel.toString (3)); predictOutput (); } function dressData () {\/ ** A row in the data object looks the same: * {* TV: &quot;10&quot;, * Radio: &quot;100&quot;, Newspaper: &quot;20&quot;, &quot;Sales&quot;: &quot;1000&quot; * } * Therefore, when adding the data points, we need to parse the value of the string as a float. * \/ csvData.forEach ((row) =&gt; {{svData.forEach X.push (f (row.Radio)); y.push (f (row.Sales));}); } function f (s) returns parseFloat (s); } function predictOutput () {rl.question (&#039;Enter input X for prediction (Press CTRL + C to exit):&#039;, (answer) =&gt; {console.log (`At X = $ {answer}, y = $ { regressionModel.predict (parseFloat (response))} `); predictOutput ();}); }\n<\/pre>\n<p>Go to your Terminal and run the index.js node and it will generate something like this:<\/p>\n<pre data-enlighter-language=\"php\" class=\"EnlighterJSRAW\">node index.js Enter the input X for the prediction (Press CTRL + C to exit): 151.5 f (x) = 0.202 * x + 9.31 Enter the input X for the prediction (Press CTRL + C to exit): At X = 151.5, y = 39.989749279911285\n<\/pre>\n<\/p><\/div>","protected":false},"excerpt":{"rendered":"<p>El d\u00eda de hoy aprenderemos acerca del Aprendizaje autom\u00e1tico en JS, y s\u00ed, si estas leyendo bien. Aprendizaje Autom\u00e1tico en JS \u00a1\u00bfJAVASCRIPT?! \u00bfNo deber\u00eda estar usando python? \u00bfEstoy loca por&#8230;<\/p>","protected":false},"author":1,"featured_media":95643,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1374],"tags":[],"class_list":["post-95642","post","type-post","status-publish","format-standard","has-post-thumbnail","category-javascript"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.0 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Aprendizaje autom\u00e1tico con JavaScript: Parte 1 - R Marketing Digital<\/title>\n<meta name=\"description\" content=\"El d\u00eda de hoy aprenderemos acerca del Aprendizaje autom\u00e1tico en JS, y s\u00ed, si estas leyendo bien. 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