Monthly Archives: February 2017

Property Based Testing in Python

Ooh, that looks cool. You could possibly use composite strategies https://hypothesis.readthedocs.org/en/master/data.html#composite-strategies for testing dataframes.

–Abie

From: Joe A. Wagner
Sent: Thursday, February 25, 2016 11:03 AM
To: Abraham D. Flaxman
Subject: property based testing

Hi Abie,

Have you seen hypothesis? It looks really useful. I’ve been meaning to incorporate it into my code, but I’m having a hard time defining properties of data frames (which is usually the input of most of my functions).

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Filed under software engineering

Journal Club: Counter-measures for Implicit Bias

This long-read from vox.com would be 13 pages if I printed it, but it is for a general audience, so it’s not like a 13 page research paper.
http://www.vox.com/identities/2016/11/15/13595508/racism-trump-research-study

Linked from the link is this amazing video:

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Filed under diversity and inclusion

Four-year-old broke, fixed my math clock

I’ve been gifted a steady stream of math clocks over the years, including a really transcendental one that has been in my dining room for quite a while. I didn’t realize how often I used it to check the time until my four-year-old broke the hands off one recent day. (“I wanted to see what happens when you bend them back and forth,” he explained, but I digress.)

The purpose of this blog is to document the *fix* for this failure that we developed together:
clock
“What time is it?”, I inattentively asked myself as a kid came down the stairs this morning. Perfect answer!

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Filed under general

New book on Probabilistic Programming

This crossed my inbox recently:

The e-book is available now from https://www.manning.com/books/practical-probabilistic-programming. The print version will be available on Friday.

>From the cover:

Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In it, you’ll learn how to use the PP paradigm to model application domains and then express those probabilistic models in code. Although PP can seem abstract, in this book you’ll immediately work on practical examples, like using the Figaro language to build a spam filter and applying Bayesian and Markov networks, to diagnose computer system data problems and recover digital images.

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Filed under TCS

Journal Club: Reducing Bias in Academic Search Committees

Short article from the kick-off of a new IHME journal club, with a focus on diversity and health disparities: [link]

Topics that bubbled up in discussion: composition of search committees, pipeline issues and other barriers to attracting diverse candidates, the scale of the problem with systemic racism.

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Filed under education

Journal Club: Ten Frequently Asked Questions About Implicit Measures and Their Frequently Supposed, But Not Entirely Correct Answers

Second edition of the Diversity Lunch Discussion journal club, with a focus on the Implicit Association Test. Many participants also *took* an IAT—Rose suggests you try taking the Race IAT before our discussion tomorrow: https://implicit.harvard.edu/implicit/takeatest.html

So much knowledge and expertise in this group.

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Filed under education

Websearch for Text Clustering

Here are some interesting results:

http://datascience.stackexchange.com/questions/979/algorithms-for-text-clustering

http://www.charuaggarwal.net/text-cluster.pdf

Anything I should add to my reading list?

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