{"id":12112,"date":"2021-05-04T09:26:51","date_gmt":"2021-05-04T13:26:51","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=12112"},"modified":"2021-05-04T10:32:07","modified_gmt":"2021-05-04T14:32:07","slug":"wise-practitioner-predictive-analytics-interview-series-daniel-rohr-at-tracks-gmbh","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wise-practitioner-predictive-analytics-interview-series-daniel-rohr-at-tracks-gmbh\/12112\/","title":{"rendered":"Wise Practitioner \u2013 Predictive Analytics Interview Series: Daniel Rohr at Tracks GmbH"},"content":{"rendered":"By: Eugene Kirpichov, Sasha Luccioni &amp; David Rolnick, Conference Chairs, Predictive Analytics World for Climate In anticipation of his upcoming presentation at Predictive Analytics World for Climate\u00a0Livestream, May 24-28, 2021,\u00a0we asked Daniel Rohr, Senior Data Scientist at Tracks GmbH, a few questions about their deployment of predictive analytics. Catch a glimpse of his presentation, Tracks For Trucks: Turning Data Science into CO2 Savings, and see what\u2019s in store at the PAW Climate conference. Q: In your work with predictive analytics, what behavior or outcome do your models predict? A: Tracks&#8217; mission is to reduce the CO2 emissions in <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wise-practitioner-predictive-analytics-interview-series-daniel-rohr-at-tracks-gmbh\/12112\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>(more&hellip;)<\/p>\n","protected":false},"author":14304,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[3,591],"tags":[],"class_list":["post-12112","post","type-post","status-publish","format-standard","hentry","category-leading-stories","category-interviews"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/12112","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\/14304"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=12112"}],"version-history":[{"count":3,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/12112\/revisions"}],"predecessor-version":[{"id":12116,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/12112\/revisions\/12116"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=12112"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=12112"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=12112"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}