Publications by Brian Lee Yung Rowe

The Data-Driven Weekly #1.6

16.12.2015

Right on cue, this past week heralded in an announcement of OpenAI, a new non-profit started by a number of tech luminaries to spearhead AI research that is publicly accessible. The motivation is that apparently these scions of capitalism lose faith in Adam Smith’s invisible hand when it comes to AI R&D. Musk continues to promote the idea that ...

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The Data-Driven Weekly #1.7

23.12.2015

Photo: Nathaniel Welch It turns out I’m not the only one who thinks AI alarmism is a bit out of hand. The ITIF Luddite Award nominations include “alarmists, even including respected luminaries such as Elon Musk and Stephen Hawking, touting an artificial intelligence apocalypse.” Opinions are stewing on both sides of the issue, with Gizmodo ...

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Big data in agriculture (DDW2.1)

05.01.2016

The Data-Driven Weekly is kicking off 2016 by exploring how big data and analytics is powering data-driven business in different industries. First off is the world of agriculture. While data has always played a prominent role in agriculture and ranching, the explosion of cheap sensors and data storage means that every aspect of agriculture can no...

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Big data in ranching and animal husbandry

20.01.2016

Another big part of the food supply comes from ranches and farms that raise and slaughter various livestock. While ranching is sometimes bundled with agriculture, I discussed farming in Big Data in Agriculture, so we’ll focus on ranching this time around. Somewhat surprising is that big data usage in ranching appears more limited than in farmin...

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7 Ways to Perplex a Data Scientist

02.02.2016

On the heels of a report showing the inefficacy of government-run cyber security, it’s imperative to understand the limitations of your system and model. As that article shows, in addition to bureaucratic risk the government also needs to worry about gaming-the-bureaucracy risk! Government snafus aside, data science has enjoyed considerable su...

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Is deep learning a Markov chain in disguise?

23.02.2016

Andrej Karpathy’s post “The Unreasonable Effectiveness of Recurrent Neural Networks” made splashes last year. The basic premise is that you can create a recurrent neural network to learn language features character-by-character. But is the resultant model any different from a Markov chain built for the same purpose? I implemented a characte...

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Using Occam’s Razor to solve genius math puzzles

04.03.2016

Math puzzles always tickle the brain, and this one has tickled quite a few on LinkedIn. Why are these puzzles so popular, and what’s the right answer? I sampled 610 responses to find out. Of the 610 responses I sampled, the range of answers was surprisingly large, although there were two clear candidates 98 and 99, followed by a less likely th...

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Modeling data with functional programming – State based systems

19.05.2016

I’m pleased to announce the availability of my latest chapter on state based systems for my book “Modeling data with functional programming in R”. This chapter is the culmination of the ideas presented in the preceding chapters and presents numerous examples. The chapter initially discusses the idea of state and how to manage it within clos...

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How to write good tests in R

30.06.2016

Testing is an often overlooked yet critical component of any software system. In some ways this is more true of models than traditional software. The reason is that computational systems must function correctly at both the system level and the model level. This article provides some guidelines and tips to increase the certainty around the correct...

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Best practices for logging computational systems in R and Python

07.07.2016

As is the case with most quant software, it’s a bit different from run-of-the-mill software. The somewhat prosaic world of logging is one such place where there are some differences. What’s different about quant systems? First, they have multiple run modes. Particularly in finance, models often run in real-time but also historically. Models m...

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