{"id":2490,"date":"2017-09-29T11:13:38","date_gmt":"2017-09-29T11:13:38","guid":{"rendered":"https:\/\/www.kolabtree.com\/blog\/?p=2490"},"modified":"2017-09-29T12:22:27","modified_gmt":"2017-09-29T12:22:27","slug":"must-read-data-science-articles-september-2017","status":"publish","type":"post","link":"https:\/\/www.kolabtree.com\/blog\/must-read-data-science-articles-september-2017\/","title":{"rendered":"10 Must-Read Data Science Articles from September 2017"},"content":{"rendered":"

The data science industry is quickly finding applications in a variety of disciplines ranging from biotechnology<\/a> to social science<\/a>. It’s revolutionized the way we make decisions both as businesses and researchers. Data science is currently the ‘best job in America’, according to Glassdoor. The amount of data that we collect is mind-boggling, not only through traditional ways but also through digital platforms and social media. Data analysis, visualization and interpretation are skills that are in high demand — and experts often specialize in specific disciplines such as computer science or even astrophysics. At Kolabtree, we’ve helped project owners find highly qualified freelance data science experts<\/a> to help them analyze a dataset or write an algorithm — and this is proof that organizations suffer from a skills or resource gap in this field.<\/p>\n

Data scientists need to keep themselves updated on the latest research<\/a> and developments in the field to stay on top of their game. Here is a curated list of the top 10 articles from September 2017 that we think is necessary reading.<\/p>\n

1.\u00a0Here are the 10 skills you need to become a data scientist, the no. 1 job in America<\/a>
\n(Alison DeNisco, TechRepublic)<\/p>\n

2.\u00a0The Abyss of Analytics\u00a0<\/a>
\n(Jon Evans, TechCrunch)<\/p>\n

3.\u00a0New Tool Uses Machine Learning And Artificial Intelligence To Improve IT Operations<\/a>
\n(Bernard Marr, Forbes)<\/p>\n

4.\u00a0Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics<\/a>
\n(Vincent Granville, Data Science Central)<\/p>\n

5.\u00a0A Wikipedia For Data Visualizations Is Here<\/a>
\n(Katharine Schwab, \u00a0Co.Design)<\/p>\n

6.\u00a0If you want to upgrade your data analysis skills, which programming language should you learn?<\/a>\u00a0[R vs Python]\n(Dan Kopf, Quartz)<\/p>\n

7.\u00a030 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets<\/a>
\n(Matthew Mayo, KDNuggets)<\/p>\n

8.\u00a0The A.I. \u201cGaydar\u201d Study and the Real Dangers of Big Data<\/a>
\n(Alan Burdick, The New Yorker)<\/p>\n

9.\u00a0Securing Competitive Advantage with Machine Learning<\/a>
\n(Ronald van Loon, Dataconomy)<\/p>\n

10.\u00a0Raiders of the storm: The data science behind weather prediction<\/a>
\n(George Anadiotis, ZDNet)<\/p>\n

Have any more articles to add to the list? Leave them in the comments below or Tweet to us<\/a>!<\/p>\n","protected":false},"excerpt":{"rendered":"

The data science industry is quickly finding applications in a variety of disciplines ranging from biotechnology to social science. It’s revolutionized the way we make decisions both as businesses and researchers. Data science is currently the ‘best job in America’, according to Glassdoor. The amount of data that we collect is mind-boggling, not only through<\/p>\n

Read More<\/a><\/div>\n","protected":false},"author":12,"featured_media":2494,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"acf":[],"yoast_head":"\n10 Must-Read Data Science Articles from September 2017 - The Kolabtree Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.kolabtree.com\/blog\/must-read-data-science-articles-september-2017\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"10 Must-Read Data Science Articles from September 2017\" \/>\n<meta property=\"og:description\" content=\"The data science industry is quickly finding applications in a variety of disciplines ranging from biotechnology to social science. 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