{"id":6908,"date":"2015-12-04T14:00:22","date_gmt":"2015-12-04T19:00:22","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=6908"},"modified":"2015-12-02T10:27:53","modified_gmt":"2015-12-02T15:27:53","slug":"the-hardest-parts-of-data-science","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/the-hardest-parts-of-data-science\/6908\/","title":{"rendered":"The Hardest Parts of Data Science"},"content":{"rendered":"Contrary to common belief, the hardest part of data science isn\u2019t building an accurate model or obtaining good, clean data. It is much harder to define feasible problems and come up with reasonable ways of measuring solutions. This post discusses some examples of these issues and how they can be addressed. The not-so-hard parts Before discussing the hardest parts of data science, it\u2019s worth quickly addressing the two main contenders: model fitting and data collection\/cleaning. Model fitting is seen by some as particularly hard, or as real data science. This belief is fuelled in part by the success <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/the-hardest-parts-of-data-science\/6908\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Contrary to common belief, the hardest part of data science isn\u2019t building an accurate model or obtaining good, clean data. It is much harder to define feasible problems and come up with reasonable ways of measuring solutions. This post discusses some examples of these issues and how they can be addressed. The not-so-hard parts Before [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11],"tags":[166,190,573,574],"class_list":["post-6908","post","type-post","status-publish","format-standard","hentry","category-industry-news","tag-data-science","tag-kaggle","tag-predictive-modelling","tag-science-communication"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6908","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=6908"}],"version-history":[{"count":1,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6908\/revisions"}],"predecessor-version":[{"id":6909,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/6908\/revisions\/6909"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=6908"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=6908"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=6908"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}