NYU Data Science newsletter – September 18, 2015

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The field of statistics has a reputation for being difficult to crack: it revolves around a seemingly endless jargon of distributions, test statistics, confidence intervals, p-values, and more, with each concept subject to its own subtle assumptions. But it doesn’t have to be this way: today we have access to computers that Neyman and Pearson could only dream of, and many of the conceptual challenges in the field can be overcome through judicious use of these CPU cycles. In this talk I’ll discuss how you can use your coding skills to “hack statistics” – to replace some of the theory and jargon with intuitive computational approaches such as sampling, shuffling, cross-validation, and Bayesian methods – and show that with a grasp of just a few fundamental concepts, if you can write a for-loop you can do statistical analysis.

Accel Partners wants to solve the question for startups, “Who does this marketing thing I need?”

It’s doing that with an online tool called Growthverse, an interactive visualization of companies in the marketing technology ecosystem. It launched earlier this year but since receiving a lot of feedback, Accel Partners has refined it with a big update today into what it hopes is a tool that helps startups navigate the complicated landscape. Founders can dig into specific areas of marketing technology, finding out which companies build the tools they need and getting a quick glance at each company.

At Trifacta, we want to revolutionize the way people and organizations work with data. Our first major step towards that end is a product that enables a new class of Big Data analysts – mixing technical and organizational innovation. Of course, understanding how companies and industries as a whole are addressing these kinds of changes helps us to direct our efforts. The industry going through arguably the largest transformation in this era of Big Data is the pharmaceutical industry given the recent advances in technology combined with government healthcare reforms. To dive deeper into the analytics challenges and opportunities that face pharmaceutical organizations, we sat down with Brian Ellerman of Sanofi to get an insider’s perspective. Included below is an excerpt of that conversation:

Pedro Domingos, University of Washington professor of computer science and engineering, is the author of “The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World.” … Domingos, who will speak at Seattle’s Town Hall at 7:30 p.m. on Sept. 22, answered a few questions about the book.