只懂机器学习就 OUT 了，下一代数据科学家得是“全栈型“

{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"人人都在谈论数据科学，没有人真正知道如何去做，每个人都认为别人在做，所以所有人都声称自己在做数据科学。"}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"italic"},{"type":"strong"}],"text":"本文最初发表于 Towards Data Science 博客，经原作者 Jay Kachhadia 授权，InfoQ 中文站翻译并分享。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"本文探讨了成为一名机器学习数据科学家需要具备的条件，以跟上行业不断变化的需求。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"多年来，对于拥有计算机科学、统计学、商业分析、工程管理、物理学、数学或数据科学学士、硕士或博士学位的年轻人而言，数据科学一直是他们的目标。然而，人们对于数据科学有很多误解。这已经不仅仅是机器学习和统计学了。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"这些年来，我已经与许多有志于数据科学领域的人讨论过要进入这个领域的想法。为什么数据科学如此火爆？或者统计学和机器学习能帮助你进入这个领域吗？它还会是未来吗？"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"即使我和你们都在同一条船上，但我现在正在体验到，目前对于下一代数据科学家进入这一领域的需求是如何形成的。我并不会教你如何进入数据科学领域，因为在互联网上，已经有很多人这样做了。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"heading","attrs":{"align":null,"level":2},"content":[{"type":"text","text":"为什么数据科学如此火爆？"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}