{"id":65752,"date":"2024-01-29T11:50:45","date_gmt":"2024-01-29T10:50:45","guid":{"rendered":"https:\/\/www.upjs.sk\/prirodovedecka-fakulta\/events\/matlab-roadshow-2024\/"},"modified":"2024-01-30T10:01:59","modified_gmt":"2024-01-30T09:01:59","slug":"matlab-roadshow-2024","status":"publish","type":"cpt_podujatia","link":"https:\/\/www.upjs.sk\/prirodovedecka-fakulta\/en\/events\/matlab-roadshow-2024\/","title":{"rendered":"MATLAB Roadshow 2024"},"content":{"rendered":"\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<style>.kadence-column65752_0d68a4-e8 > .kt-inside-inner-col,.kadence-column65752_0d68a4-e8 > .kt-inside-inner-col:before{border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-right-radius:0px;border-bottom-left-radius:0px;}.kadence-column65752_0d68a4-e8 > .kt-inside-inner-col{column-gap:var(--global-kb-gap-sm, 1rem);}.kadence-column65752_0d68a4-e8 > .kt-inside-inner-col{flex-direction:column;}.kadence-column65752_0d68a4-e8 > .kt-inside-inner-col > .aligncenter{width:100%;}.kadence-column65752_0d68a4-e8 > .kt-inside-inner-col:before{opacity:0.3;}.kadence-column65752_0d68a4-e8{position:relative;}@media all and (max-width: 1024px){.kadence-column65752_0d68a4-e8 > .kt-inside-inner-col{flex-direction:column;}}@media all and (max-width: 767px){.kadence-column65752_0d68a4-e8 > .kt-inside-inner-col{flex-direction:column;}}<\/style>\n<div class=\"wp-block-kadence-column kadence-column65752_0d68a4-e8\"><div class=\"kt-inside-inner-col\">\n<p class=\"has-text-align-center\">Lecture title: <strong>Data analytics in MATLAB environment<\/strong><\/p>\n\n\n\n<p class=\"has-text-align-center\">Date:  <strong>\u00a013.2.2024,\u00a0 from 14:00 p.m. to 16:00 p.m.<\/strong><\/p>\n\n\n\n<p class=\"has-text-align-center\">Location:<strong>\u00a0The study room A. Merici, PA9<\/strong><\/p>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-65752_1de3a6-e2 .kt-block-spacer{height:30px;}.wp-block-kadence-spacer.kt-block-spacer-65752_1de3a6-e2 .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-65752_1de3a6-e2\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\"\/><\/div><\/div>\n\n\n\n<p class=\"has-text-align-justify\">Abstract:Data processing brings several challenges. Data can be located in many different places and often needs to be edited before it can be used. Depending on the type of data, an algorithm needs to be chosen to process it. Various prediction models based on machine learning and Deep Learning are trending. The algorithm often needs to be scaled and deployed in different types of applications.<br>During the workshop, we will demonstrate the capabilities of the MATLAB environment for data analytics:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Accessing data in files, databases or from measurement devices<\/li>\n\n\n\n<li>working with raw data (missing data, noise, drift)<\/li>\n\n\n\n<li>creating algorithms for image, signal and other types of data processing<\/li>\n\n\n\n<li>working with artificial intelligence algorithms &#8211; machine learning and deep learning<\/li>\n\n\n\n<li>scaling algorithms for big data (Big Data) &#8211; integrating algorithms into applications.<\/li>\n<\/ul>\n<\/div><\/div>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<style>.kadence-column65752_bbbe27-98 > .kt-inside-inner-col{display:flex;}.kadence-column65752_bbbe27-98 > .kt-inside-inner-col,.kadence-column65752_bbbe27-98 > 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