内容简介：Chris Wiggins is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at The New York Times. At Columbia he is a founding member of the executive committee of the Data Science Institute, and of the Department of
About the speaker
Chris Wiggins is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at The New York Times. At Columbia he is a founding member of the executive committee of the Data Science Institute, and of the Department of Applied Physics and Applied Mathematics as well as the Department of Systems Biology, and is affiliated faculty in Statistics. https://www.linkedin.com/in/wiggins/
About the talk
The Data Science group at The New York Times develops and deploys machine learning solutions to newsroom and business problems. Re-framing real-world questions as machine learning tasks require not only adapting and extending models and algorithms to new or special cases but also sufficient breadth to know the right method for the right challenge. The speaker will first outline how unsupervised, supervised, and reinforcement learning methods are increasingly used in human applications for description, prediction, and prescription, respectively. The speaker will then focus on the ‘prescriptive’ cases, showing how methods from the reinforcement learning and causal inference literatures can be of direct impact in engineering, business, and decision-making more generally.
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Unix/Linux编程实践教程
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操作系统是计算机最重要的系统软件。Unix操作系统历经了几十年，至今仍是主流的操作系统。本书通过解释Unix的工作原理，循序渐进地讲解实现Unix中系统命令的方法，让读者理解并逐步精通Unix系统编程，进而具有编制Unix应用程序的能力。书中采用启发式、举一反三、图示讲解等多种方法讲授，语言生动、结构合理、易于理解。每一章后均附有大量的习题和编程练习，以供参考。 本书适合作为高等院校计算机及......一起来看看 《Unix/Linux编程实践教程》 这本书的介绍吧!
