{"id":6786,"date":"2024-03-15T07:17:30","date_gmt":"2024-03-15T07:17:30","guid":{"rendered":"https:\/\/www.pickl.ai\/blog\/?post_type=web-story&#038;p=6786"},"modified":"2024-03-15T07:17:31","modified_gmt":"2024-03-15T07:17:31","slug":"machine-learning-interview-questions","status":"publish","type":"web-story","link":"https:\/\/www.pickl.ai\/blog\/web-stories\/machine-learning-interview-questions\/","title":{"rendered":"Machine Learning Interview Questions"},"content":{"rendered":"<p><html amp=\"\" lang=\"en\"><head><meta charSet=\"utf-8\"\/><meta name=\"viewport\" content=\"width=device-width,minimum-scale=1,initial-scale=1\"\/><script async=\"\" src=\"https:\/\/cdn.ampproject.org\/v0.js\"><\/script><script async=\"\" src=\"https:\/\/cdn.ampproject.org\/v0\/amp-story-1.0.js\" custom-element=\"amp-story\"><\/script><link href=\"https:\/\/fonts.googleapis.com\/css2?display=swap&amp;family=Roboto%3Awght%40700&amp;family=Alegreya%3Awght%40400%3B700\" rel=\"stylesheet\"\/>\n<style amp-boilerplate=\"\">body{-webkit-animation:-amp-start 8s steps(1,end) 0s 1 normal both;-moz-animation:-amp-start 8s steps(1,end) 0s 1 normal both;-ms-animation:-amp-start 8s steps(1,end) 0s 1 normal both;animation:-amp-start 8s steps(1,end) 0s 1 normal both}@-webkit-keyframes -amp-start{from{visibility:hidden}to{visibility:visible}}@-moz-keyframes -amp-start{from{visibility:hidden}to{visibility:visible}}@-ms-keyframes -amp-start{from{visibility:hidden}to{visibility:visible}}@-o-keyframes -amp-start{from{visibility:hidden}to{visibility:visible}}@keyframes -amp-start{from{visibility:hidden}to{visibility:visible}}<\/style>\n<p><noscript><\/p>\n<style amp-boilerplate=\"\">body{-webkit-animation:none;-moz-animation:none;-ms-animation:none;animation:none}<\/style>\n<p><\/noscript><\/p>\n<style amp-custom=\"\">\n              h1, h2, h3 { font-weight: normal; }<\/p>\n<p>              amp-story-page {\n                background-color: #131516;\n              }<\/p>\n<p>              amp-story-grid-layer {\n                overflow: visible;\n              }<\/p>\n<p>              @media (max-aspect-ratio: 9 \/ 16)  {\n                @media (min-aspect-ratio: 320 \/ 678) {\n                  amp-story-grid-layer.grid-layer {\n                    margin-top: calc((100% \/ 0.5625 - 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(2 * 74px));\n              }<\/p>\n<p>              .captions-area {\n                padding: 0 32px 0;\n              }<\/p>\n<p>              amp-story-captions {\n                margin-bottom: 16px;\n                text-align: center;\n              }\n              <\/style>\n<p><meta name=\"web-stories-replace-head-start\"\/><title>Machine Learning Interview Questions<br \/>\n<\/title><link rel=\"canonical\" href=\"https:\/\/pickl.ai\/blog\/?post_type=web-story&amp;p=6786\"\/><meta name=\"web-stories-replace-head-end\"\/><\/head><body><amp-story standalone=\"\" publisher=\"Pickl.AI\" publisher-logo-src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2022\/01\/cropped-cropped-favicon.png\" title=\"Machine Learning Interview Questions\n\" poster-portrait-src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/cropped-771-scaled-1.jpg\"><amp-story-page id=\"dd712fcb-41c5-4eb6-8280-c76de8040305\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#6591b6\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-6bed8ab2-c51c-405a-b7a3-4ebdd9713e6c\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:10.67961%;top:4.85437%;width:77.6699%;height:39.80583%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-57a9982b-8534-433a-bb06-986359d84f6e\">\n<div style=\"position:absolute;width:102.50002%;height:100%;left:-1.25001%;top:0%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/771-scaled.jpg\" alt=\"\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/771-scaled.jpg 2560w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/771-2048x1536.jpg 2048w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/771-1536x1152.jpg 1536w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/771-1024x768.jpg 1024w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/771-768x576.jpg 768w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/771-300x225.jpg 300w\" sizes=\"(min-width: 1024px) 35vh, 78vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:7.52427%;top:50%;width:83.98058%;height:23.6246%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.5780346820809248% 0.5780346820809248% 0.5780346820809248% 0.5780346820809248% \/ 1.36986301369863% 1.36986301369863% 1.36986301369863% 1.36986301369863%\" id=\"el-31f7b171-b097-4b74-8bec-bbe5da9846a1\">\n<h1 id=\"machine-learning-interview-questions\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.1073880057803467% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.663430em;line-height:1.19;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #fff\">Machine Learning Interview Questions<\/span><\/span><\/h1>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:23.05825%;top:78.9644%;width:65.29126%;height:16.50485%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.7434944237918215% 0.7434944237918215% 0.7434944237918215% 0.7434944237918215% \/ 1.9607843137254901% 1.9607843137254901% 1.9607843137254901% 1.9607843137254901%\" id=\"el-31c7a4ca-1903-4d1e-8b11-5facb23aeff3\">\n<h2 id=\"land-your-dream-job-brush-up-on-common-machine\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.8079925650557623% 0;font-family:&quot;Alegreya&quot;,serif;font-size:0.436893em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">Land your dream job. Brush up on common Machine<\/span><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"6070e3b0-e960-4ba4-9ef8-68122fead1ca\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#a676a7\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-5aa2b1c6-8a64-40fd-ad18-2f4dc0a01a1a\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:42.55663%;width:75.72816%;height:13.91586%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.641025641025641% 0.641025641025641% 0.641025641025641% 0.641025641025641% \/ 2.3255813953488373% 2.3255813953488373% 2.3255813953488373% 2.3255813953488373%\" id=\"el-1f35cf1e-fd73-46dc-ad94-4121ae4a72ff\">\n<h1 id=\"explain-the-bias-variance-tradeoff\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.1045673076923071% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.582524em;line-height:1.19;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #fff\">Explain the bias-variance tradeoff<\/span><\/span><\/h1>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.8932%;top:0;width:76.45631%;height:36.56958%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-20c16edf-5b53-4f09-9b4a-ccba5f34b8bc\">\n<div style=\"position:absolute;width:107.59804%;height:100%;left:-3.79902%;top:0%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/market-share-competitor-excellent-growing-with-stocks-scaled.jpg\" alt=\"\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/market-share-competitor-excellent-growing-with-stocks-scaled.jpg 2560w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/market-share-competitor-excellent-growing-with-stocks-2048x1365.jpg 2048w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/market-share-competitor-excellent-growing-with-stocks-1536x1024.jpg 1536w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/market-share-competitor-excellent-growing-with-stocks-1024x683.jpg 1024w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/market-share-competitor-excellent-growing-with-stocks-768x512.jpg 768w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/market-share-competitor-excellent-growing-with-stocks-300x200.jpg 300w\" sizes=\"(min-width: 1024px) 34vh, 76vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:18.93204%;top:61.8123%;width:64.56311%;height:27.6699%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.7518796992481203% 0.7518796992481203% 0.7518796992481203% 0.7518796992481203% \/ 1.1695906432748537% 1.1695906432748537% 1.1695906432748537% 1.1695906432748537%\" id=\"el-01d59314-9dd5-4b5e-8f06-e4e9badbe953\">\n<p class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.6052631578947366% 0;font-family:&quot;Alegreya&quot;,serif;font-size:0.323625em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #ffd900\">Bias refers to the error introduced by approximating a real-world problem with a simplified model. While variance refers to the model\u2019s sensitivity to fluctuations in the training data.<\/span><\/span><\/p>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:18.93204%;top:94.82201%;width:42.96117%;height:5.01618%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:1.1299435028248588% 1.1299435028248588% 1.1299435028248588% 1.1299435028248588% \/ 6.451612903225806% 6.451612903225806% 6.451612903225806% 6.451612903225806%\" id=\"el-6fbbb77b-3e29-4f74-9b38-15e6da3f5d80\"><a href=\"https:\/\/pickl.ai\/blog\/machine-learning-interview-questions-ace-your-next-interview\/\" data-tooltip-icon=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/image1-1.png\" data-tooltip-text=\"Machine Learning interview questions: Ace your next interview\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.2145127118644064% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.436893em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #fff\">Learn More&nbsp;<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"28e4a0d1-ecc8-4898-a645-c178fe88cfe8\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#4f9e88\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-8e5d6500-e0fb-43a6-92df-7da55c732452\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:14.32039%;top:46.1165%;width:75.72816%;height:11.16505%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.641025641025641% 0.641025641025641% 0.641025641025641% 0.641025641025641% \/ 2.898550724637681% 2.898550724637681% 2.898550724637681% 2.898550724637681%\" id=\"el-98c436ef-3632-4642-b408-15b6b8165c1c\">\n<h2 id=\"how-do-you-handle-imbalanced-datasets\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.08423477564102533% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.469256em;line-height:1.19;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #fff\">How do you handle imbalanced datasets?<\/span><\/span><\/h2>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:17.23301%;top:61.48867%;width:70.14563%;height:30.09709%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6920415224913495% 0.6920415224913495% 0.6920415224913495% 0.6920415224913495% \/ 1.0752688172043012% 1.0752688172043012% 1.0752688172043012% 1.0752688172043012%\" id=\"el-94c1ed5f-f4d0-4432-a393-facaa482546c\">\n<h3 id=\"imbalanced-datasets-can-trick-machine-learning-models-to-overcome-this-you-can1-reduce-the-majority-class-examples-undersampling2-increase-the-minority-class-examples-oversampling\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.5849480968858132% 0;font-family:&quot;Alegreya&quot;,serif;font-size:0.339806em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #ffd900\">Imbalanced datasets can trick machine learning models. To overcome this you can:<\/span><br \/>\n<span style=\"font-weight: 700; color: #ffd900\">1. &nbsp;Reduce the majority class examples (undersampling)<\/span><br \/>\n<span style=\"font-weight: 700; color: #ffd900\">2. &nbsp;Increase the minority class examples (oversampling)<\/span><\/span><\/h3>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:28.64078%;top:94.98382%;width:42.96117%;height:5.01618%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:1.1299435028248588% 1.1299435028248588% 1.1299435028248588% 1.1299435028248588% \/ 6.451612903225806% 6.451612903225806% 6.451612903225806% 6.451612903225806%\" id=\"el-1fc68e73-eb9b-4a24-99ed-9ca6315c048e\"><a href=\"https:\/\/pickl.ai\/blog\/best-machine-learning-frameworks\/\" data-tooltip-icon=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2023\/01\/MACHINE-LEARNING-FRAMEWORK.jpg\" data-tooltip-text=\"Top Machine Learning Frameworks for 2023- Pickl.AI\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more-2\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.2145127118644064% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.436893em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #fff\">Learn More&nbsp;<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:0;width:75.72816%;height:38.83495%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-eb036a33-be8f-4373-9540-d9136ef90b32\">\n<div style=\"position:absolute;width:100%;height:130.00001%;left:0%;top:-15.00001%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/9229545.jpg\" alt=\"\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"30901910-363c-4af8-b5da-05fa896a09f8\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#fdba3b\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-6163e185-0193-45f2-8cb9-03c1e6f055dc\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:15.29126%;top:47.73463%;width:74.27184%;height:12.45955%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6535947712418301% 0.6535947712418301% 0.6535947712418301% 0.6535947712418301% \/ 2.5974025974025974% 2.5974025974025974% 2.5974025974025974% 2.5974025974025974%\" id=\"el-4d9fe2f9-95c4-46db-ab41-9c62a985a156\">\n<h2 id=\"what-are-ensemble-learning-methods\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.09477124183006508% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.517799em;line-height:1.19;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #fff\">What are ensemble learning methods?<\/span><\/span><\/h2>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:15.29126%;top:63.43042%;width:70.14563%;height:26.3754%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6920415224913495% 0.6920415224913495% 0.6920415224913495% 0.6920415224913495% \/ 1.2269938650306749% 1.2269938650306749% 1.2269938650306749% 1.2269938650306749%\" id=\"el-acb3cdd5-0cc5-4e4a-9a69-d39f6c618367\">\n<p class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.529238754325259% 0;font-family:&quot;Alegreya&quot;,serif;font-size:0.307443em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">Ensemble learning methods are a ML technique that combines predictions from multiple models to create a more accurate prediction. There are three main categories of ensemble methods: bagging, boosting, and stacking.<\/span><\/span><\/p>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:28.64078%;top:94.98382%;width:42.96117%;height:5.01618%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:1.1299435028248588% 1.1299435028248588% 1.1299435028248588% 1.1299435028248588% \/ 6.451612903225806% 6.451612903225806% 6.451612903225806% 6.451612903225806%\" id=\"el-65ab4fe1-dfe1-45ba-ad4a-667bff569abe\"><a href=\"https:\/\/pickl.ai\/blog\/sailing-into-2024-machine-learning-salary-trends-unveiled\/\" data-tooltip-icon=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/01\/machine-learning.jpg\" data-tooltip-text=\"Sailing into 2024: Machine Learning salary trends unveiled\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more-3\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.2145127118644064% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.436893em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #fff\">Learn More&nbsp;<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:0;width:75.72816%;height:42.0712%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-d5f6e2cb-ddce-4af6-ac83-b9e0aed08b53\">\n<div style=\"position:absolute;width:100%;height:120%;left:0%;top:-10%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/12063788_4893415.jpg\" alt=\"12063788_4893415\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/12063788_4893415.jpg 2000w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/12063788_4893415-1536x1536.jpg 1536w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/12063788_4893415-1024x1024.jpg 1024w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/12063788_4893415-768x768.jpg 768w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/12063788_4893415-300x300.jpg 300w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/12063788_4893415-150x150.jpg 150w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/12063788_4893415-96x96.jpg 96w\" sizes=\"(min-width: 1024px) 34vh, 76vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"66810dfc-4155-46a4-adef-5fc60eb7fbda\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#f2d6e1\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-269e452e-0337-454d-8aeb-8c5d35e56a62\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:14.07767%;top:41.58576%;width:77.6699%;height:16.01942%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.625% 0.625% 0.625% 0.625% \/ 2.0202020202020203% 2.0202020202020203% 2.0202020202020203% 2.0202020202020203%\" id=\"el-4fb12876-ee27-4ab3-821d-95208c750bf7\">\n<h2 id=\"what-evaluation-metrics-would-you-use-for-this-recommender-system\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.07929687500000004% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.453074em;line-height:1.19;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700; color: #e03568\">What evaluation metrics would you use for this recommender system?<\/span><\/span><\/h2>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:16.50485%;top:64.23948%;width:67.47573%;height:26.86084%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.7194244604316548% 0.7194244604316548% 0.7194244604316548% 0.7194244604316548% \/ 1.2048192771084338% 1.2048192771084338% 1.2048192771084338% 1.2048192771084338%\" id=\"el-54cf595d-f2c1-4bac-9898-019604161f62\">\n<p class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.49226618705036007% 0;font-family:&quot;Alegreya&quot;,serif;font-size:0.275081em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span>\u2013 <span style=\"font-weight: 700\">Accuracy (RMSE\/MAE):<\/span> Measures how well predicted ratings match actual ratings. Good for absolute rating prediction.<br \/>\n<span style=\"font-weight: 700\">Ranking (MAP\/NDCG):<\/span> Evaluates how well the most relevant items are ranked at the top of recommendations. Better for item ordering.<\/span><\/p>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:11.8932%;top:-0.48544%;width:76.45631%;height:36.56958%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-b03a4196-3267-472b-bbe4-df5bbc16efdf\">\n<div style=\"position:absolute;width:107.59804%;height:100%;left:-3.79902%;top:0%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-scaled.jpg\" alt=\"19948929_6162910\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-scaled.jpg 2560w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-2048x1365.jpg 2048w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-1536x1024.jpg 1536w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-1024x683.jpg 1024w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-900x600.jpg 900w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-768x512.jpg 768w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-300x200.jpg 300w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/02\/19948929_6162910-150x100.jpg 150w\" sizes=\"(min-width: 1024px) 34vh, 76vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><amp-story-page id=\"2b48b795-4abf-4833-9566-8045daed9e0c\" auto-advance-after=\"7s\"><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\" style=\"background-color:#b9def1\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:0;top:-9.25926%;width:100%;height:118.51852%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-0a2c7cd3-d700-4902-a61a-f6cccb78945a\">\n<div class=\"fill\" style=\"will-change:transform\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><amp-story-grid-layer template=\"vertical\" aspect-ratio=\"412:618\" class=\"grid-layer\"><\/p>\n<div class=\"page-fullbleed-area\">\n<div class=\"page-safe-area\">\n<div style=\"position:absolute;pointer-events:none;left:11.65049%;top:47.08738%;width:72.3301%;height:12.62136%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.6711409395973155% 0.6711409395973155% 0.6711409395973155% 0.6711409395973155% \/ 2.564102564102564% 2.564102564102564% 2.564102564102564% 2.564102564102564%\" id=\"el-e6d2bfc6-32c1-4099-a30d-058a4f0e1bc3\">\n<h2 id=\"what-is-the-roc-curve\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.10035654362416041% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.533981em;line-height:1.19;text-align:center;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">What is the ROC curve?<\/span><\/span><\/h2>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:16.26214%;top:64.72492%;width:67.47573%;height:23.6246%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:0.7194244604316548% 0.7194244604316548% 0.7194244604316548% 0.7194244604316548% \/ 1.36986301369863% 1.36986301369863% 1.36986301369863% 1.36986301369863%\" id=\"el-f7ce2a1c-cae9-4a01-a48e-0fe1699d7a0c\">\n<p class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:0.49226618705036007% 0;font-family:&quot;Alegreya&quot;,serif;font-size:0.275081em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">The ROC curve is a graph for binary classifiers that shows the trade-off between catching true positives (benefits) vs. false positives (costs) as a classification threshold varies. A perfect classifier lands in the top left corner.<\/span><\/span><\/p>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:10.92233%;top:0;width:78.39806%;height:42.0712%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0\" class=\"mask\" id=\"el-8606a8bd-6ebf-4445-9974-21a051b9d567\">\n<div style=\"position:absolute;width:135.2322%;height:100%;left:-17.6161%;top:0%\" data-leaf-element=\"true\"><amp-img layout=\"fill\" src=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/image6.png\" alt=\"\" srcSet=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/image6.png 378w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/image6-300x179.png 300w,https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2024\/03\/image6-150x89.png 150w\" sizes=\"(min-width: 1024px) 35vh, 78vw\" disable-inline-width=\"true\"><\/amp-img><\/div>\n<\/div>\n<\/div>\n<div style=\"position:absolute;pointer-events:none;left:32.28155%;top:94.98382%;width:35.19417%;height:5.01618%;opacity:1\">\n<div style=\"pointer-events:initial;width:100%;height:100%;display:block;position:absolute;top:0;left:0;z-index:0;border-radius:1.3793103448275863% 1.3793103448275863% 1.3793103448275863% 1.3793103448275863% \/ 6.451612903225806% 6.451612903225806% 6.451612903225806% 6.451612903225806%\" id=\"el-2e704455-90cb-4aac-a25a-c363f4a4c439\"><a href=\"https:\/\/pickl.ai\/blog\/feature-scaling-in-machine-learning\/\" data-tooltip-icon=\"https:\/\/pickl.ai\/blog\/wp-content\/uploads\/2023\/08\/Feature-Scaling-in-Machine-Learning.jpg\" data-tooltip-text=\"Feature Scaling in Machine Learning- Pickl.AI\" target=\"_blank\" rel=\"noreferrer noopener\" style=\"width:100%;height:100%;display:block;position:absolute;top:0;left:0\"><\/p>\n<h2 id=\"learn-more-4\" class=\"fill text-wrapper\" style=\"white-space:pre-line;overflow-wrap:break-word;word-break:break-word;margin:-0.26185344827586154% 0;font-family:&quot;Roboto&quot;,&quot;Helvetica Neue&quot;,&quot;Helvetica&quot;,sans-serif;font-size:0.436893em;line-height:1.2;text-align:left;padding:0;color:#000000\"><span><span style=\"font-weight: 700\">Learn More<\/span><\/span><\/h2>\n<p><\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><\/amp-story-grid-layer><\/amp-story-page><\/amp-story><\/body><\/html><\/p>\n","protected":false},"excerpt":{"rendered":"Want to ace your next machine learning interview? Featuring the best Machine Learning interview questions and expert views.\n","protected":false},"author":1,"featured_media":6802,"template":"","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"web_stories_publisher_logo":935,"web_stories_poster":[],"web_stories_products":[],"footnotes":""},"web_story_category":[],"web_story_tag":[],"class_list":["post-6786","web-story","type-web-story","status-publish","has-post-thumbnail"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.3 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Machine Learning Interview Questions - Pickl.AI<\/title>\n<meta name=\"description\" content=\"Want to ace your next machine learning interview? 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