{"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\/fr\/must-read-data-science-articles-september-2017\/","title":{"rendered":"10 articles incontournables sur la science des donn\u00e9es de septembre 2017."},"content":{"rendered":"

Le secteur de la science des donn\u00e9es trouve rapidement des applications dans une vari\u00e9t\u00e9 de disciplines, allant des biotechnologie<\/a> \u00e0 sciences sociales<\/a>. Elle a r\u00e9volutionn\u00e9 la fa\u00e7on dont nous prenons des d\u00e9cisions, tant en tant qu'entreprises que chercheurs. La science des donn\u00e9es est actuellement le \"meilleur emploi en Am\u00e9rique\", selon Glassdoor. La quantit\u00e9 de donn\u00e9es que nous collectons est \u00e9poustouflante, non seulement par les moyens traditionnels mais aussi par les plateformes num\u00e9riques et les m\u00e9dias sociaux. L'analyse, la visualisation et l'interpr\u00e9tation des donn\u00e9es sont des comp\u00e9tences tr\u00e8s demand\u00e9es - et les experts se sp\u00e9cialisent souvent dans des disciplines sp\u00e9cifiques comme l'informatique ou m\u00eame l'astrophysique. Chez Kolabtree, nous avons aid\u00e9 des porteurs de projets \u00e0 trouver des freelances hautement qualifi\u00e9s. experts en science des donn\u00e9es<\/a> pour les aider \u00e0 analyser un ensemble de donn\u00e9es ou \u00e0 \u00e9crire un algorithme - et cela prouve que les organisations souffrent d'un manque de comp\u00e9tences ou de ressources dans ce domaine.<\/p>\n

Data scientists need to keep themselves updated on the latest recherche<\/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.\u00a0Voici les 10 comp\u00e9tences dont vous avez besoin pour devenir un data scientist, le poste n\u00b0 1 en Am\u00e9rique. 1 des emplois en Am\u00e9rique<\/a>
\n(Alison DeNisco, TechRepublic)<\/p>\n

2.\u00a0L'ab\u00eeme de l'analytique\u00a0<\/a>
\n(Jon Evans, TechCrunch)<\/p>\n

3.\u00a0Un nouvel outil utilise l'apprentissage automatique et l'intelligence artificielle pour am\u00e9liorer les op\u00e9rations informatiques<\/a>
\n(Bernard Marr, Forbes)<\/p>\n

4.\u00a0Diff\u00e9rence entre apprentissage automatique, science des donn\u00e9es, IA, apprentissage profond et statistiques<\/a>
\n(Vincent Granville, Data Science Central)<\/p>\n

5.\u00a0Un Wikipedia pour les visualisations de donn\u00e9es est l\u00e0<\/a>
\n(Katharine Schwab, Co.Design)<\/p>\n

6.\u00a0Si vous souhaitez am\u00e9liorer vos comp\u00e9tences en mati\u00e8re d'analyse de donn\u00e9es, quel langage de programmation devriez-vous apprendre ?<\/a>\u00a0R vs Python]\n(Dan Kopf, Quartz)<\/p>\n

7.\u00a030 antis\u00e8ches essentielles en mati\u00e8re de science des donn\u00e9es, d'apprentissage automatique et d'apprentissage profond.<\/a>
\n(Matthew Mayo, KDNuggets)<\/p>\n

8.\u00a0L'\u00e9tude \"Gaydar\" de l'IA et les vrais dangers du Big Data<\/a>
\n(Alan Burdick, The New Yorker)<\/p>\n

9.\u00a0Assurer un avantage concurrentiel gr\u00e2ce \u00e0 l'apprentissage automatique<\/a>
\n(Ronald van Loon, Dataconomy)<\/p>\n

10.\u00a0Les pirates de la temp\u00eate : La science des donn\u00e9es derri\u00e8re les pr\u00e9visions m\u00e9t\u00e9orologiques<\/a>
\n(George Anadiotis, ZDNet)<\/p>\n

Vous avez d'autres articles \u00e0 ajouter \u00e0 la liste ? Laissez-les dans les commentaires ci-dessous ou Tweetez-nous<\/a>!<\/p>","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

Lire la suite<\/a><\/div>","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\/fr\/must-read-data-science-articles-september-2017\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\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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