{"id":433,"date":"2015-02-22T13:42:07","date_gmt":"2015-02-22T18:42:07","guid":{"rendered":"http:\/\/courses.digitaldavidson.net\/dig210\/?p=433"},"modified":"2015-02-22T13:54:15","modified_gmt":"2015-02-22T18:54:15","slug":"data-is-the-oxygen-to-machine-learnings-fire","status":"publish","type":"post","link":"https:\/\/courses.digitaldavidson.net\/dig210\/2015\/02\/22\/data-is-the-oxygen-to-machine-learnings-fire\/","title":{"rendered":"Data is the Oxygen to Machine Learning’s Fire"},"content":{"rendered":"
\"cat<\/a>
YouTube’s Conception of “Cat”<\/figcaption><\/figure>\n

This past week’s discussion of Big Data seems incomplete without mentioning machine learning. For the uninitiated, machine learning is a method of computing that “trains” algorithms to achieve a desired result using large amounts of data. While machine learning has been around since 1959, it has only recently come back into fashion as businesses are waking up to its potential<\/a>\u00a0in the age of Big Data.<\/p>\n

\"MLB<\/a><\/p>\n

The key ingredient in effective machine learning applications, from FaceBook<\/a> to Baidu<\/a>, is data. Lots of data. Because of their scale, these\u00a0companies are able to gather trillions of data points for everything, including\u00a0individuals’ emotions, shopping habits, facial features and much more. To a human, or even an army of humans, one trillion pictures of peoples’ faces would yield little utility. But, to an elite team of computer scientists, such pictures allow them to construct systems that can recognize identity and emotion more accurately<\/a>, and at exponentially greater scale, than human beings.<\/p>\n

The paradigmatic shift from silos of individual networks to aggregated data and computing resources known as cloud computing<\/a>\u00a0brings with it greater efficiency and more data. Joseph Sirosh, Microsoft’s VP of Machine Learning, was recently interviewed <\/a>by the cloud and data experts at\u00a0GigaOM. Sirosh\u00a0explains that Microsoft is rapidly transitioning from an operating system provider to a cloud provider with expertise in big data and machine learning. He goes so far as to state that computing itself\u00a0is less important than the data that it provides:<\/p>\n

\u201cI think you should even first ask, \u2018How big is the world of data to computing itself?’\u201d he said. \u201cI would say that in the future, a huge part of the value being generated in the field of computing . . . is going to come from data, as opposed to storage and operating systems and basic infrastructure. It\u2019s the data that is most valuable.”<\/p><\/blockquote>\n

Microsoft has made its billions by providing software and services. Pivoting the business model of\u00a0a $360B company is a herculean task; it’s safe to say that Microsoft and every other major player in technology wouldn’t be chasing\u00a0desperately<\/a> after data science if it wasn’t a huge deal. Data is\u00a0often described as the new oil of the 21st century – machine learning is the new refinery.<\/p>\n

<\/p>\n

My colleague Scott Patrick’s\u00a0Procrastination Nation?<\/em><\/a> post would seem apropos – apologies for the delayed response!<\/p>\n","protected":false},"excerpt":{"rendered":"

This past week’s discussion of Big Data seems incomplete without mentioning machine learning. For the uninitiated, machine learning is a method of computing that “trains” algorithms to achieve a desired result using large amounts of data. While machine learning has been around since 1959, it has only recently come back into fashion as businesses are … Continue reading Data is the Oxygen to Machine Learning’s Fire<\/span><\/a><\/p>\n","protected":false},"author":14,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14,6],"tags":[],"class_list":["post-433","post","type-post","status-publish","format-standard","hentry","category-group-1","category-responders"],"_links":{"self":[{"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/posts\/433","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/comments?post=433"}],"version-history":[{"count":8,"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/posts\/433\/revisions"}],"predecessor-version":[{"id":444,"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/posts\/433\/revisions\/444"}],"wp:attachment":[{"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/media?parent=433"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/categories?post=433"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/courses.digitaldavidson.net\/dig210\/wp-json\/wp\/v2\/tags?post=433"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}