{"id":4593,"date":"2014-04-25T13:07:48","date_gmt":"2014-04-25T17:07:48","guid":{"rendered":"http:\/\/blog.local\/?p=4593"},"modified":"2014-04-25T13:07:48","modified_gmt":"2014-04-25T17:07:48","slug":"what-is-good","status":"publish","type":"post","link":"https:\/\/blog.local\/what-is-good\/","title":{"rendered":"What is good?"},"content":{"rendered":"<p>We\u2019ve been playing around with <a href=\"http:\/\/en.wikipedia.org\/wiki\/Machine_learning\" target=\"_blank\">Machine Learning<\/a>, to help uncover patterns in content.<\/p>\n<p>And there\u2019s two significant components<br \/>\n1) Definition<br \/>\n2) How variables stack up against that definition<\/p>\n<p>You can look at the elements, imagine you want to use machine learning to find out how to build a good car.<\/p>\n<p>You would load up all the good cars, that within itself is a definition, what is good?<\/p>\n<p>It could be design lead, which could be established through design awards, or design nominations, it could be sales, it could be publicity.<\/p>\n<p>Something quantifiable.<\/p>\n<p>Then you break down it down to detect all the variables that make up a good car, things like four wheels, the gradient of the curves, acceleration, weight, colour.<\/p>\n<p>This helps you then understand what a good car looks like.<\/p>\n<p>But good is subjective.<\/p>\n<p>Just remember that, data analysis is great but it always comes back to what are we doing it for.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We\u2019ve been playing around with Machine Learning, to help uncover patterns in content. And there\u2019s two significant components 1) Definition 2) How variables stack up against that definition You can look at the elements, imagine you want to use machine learning to find out how to build a good car. You would load up all [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[65,732],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/posts\/4593"}],"collection":[{"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/comments?post=4593"}],"version-history":[{"count":0,"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/posts\/4593\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/media?parent=4593"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/categories?post=4593"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.local\/wp-json\/wp\/v2\/tags?post=4593"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}