1.0KaLabshttps://karthicklakshmanan.comkarthickhttps://karthicklakshmanan.com/index.php/author/karthick/rich600338<blockquote class="wp-embedded-content" data-secret="OVOPHfdNmT"><a href="https://karthicklakshmanan.com/index.php/knowledge-base/what-is-machine-learning/">What is machine learning?</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://karthicklakshmanan.com/index.php/knowledge-base/what-is-machine-learning/embed/#?secret=OVOPHfdNmT" width="600" height="338" title="“What is machine learning?” — KaLabs" data-secret="OVOPHfdNmT" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! This file is auto-generated */ !function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document); </script> Introduction Machine learning is a subfield of artificial intelligence (AI) that focuses on developing algorithms and statistical models that enable computers to perform tasks without explicit programming. The primary goal of machine learning is to enable computers to learn and improve from experience, allowing them to make predictions, decisions, or perform specific tasks without being explicitly programmed for each case. In traditional programming, humans write explicit code to instruct a computer on how to perform a specific task. In contrast, machine learning algorithms learn from data, identifying patterns and making predictions or decisions based on that data. There are several types of machine learning approaches: Machine learning is applied in various domains, including image and speech recognition, natural language processing, recommendation systems, autonomous vehicles, medical diagnosis, and many others. It plays a crucial role in enabling computers to make sense of complex and large datasets, extracting meaningful patterns and insights.