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Matt Blodgett: But Where Do People Work in This Office?
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Sublime: Nice Features & Plugins: A brief talk introducing my favorite editor.
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Time: Programmers all hate time, timezones, etc.
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Last year, I published nine interviews with Internet friends about how an academically-minded, 22-year-old college senior should work on a Ph.D.
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Sketching as a Tool for Numerical Linear Algebra: A neat paper on sketching algorithms for linear algebra.
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How do I draw a pair of buttocks?
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brushfire: Avi Bryant has been building a ‘Brushfire is a framework for distributed supervised learning of decision tree ensemble models in Scala.’
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There’s no magic: virtualenv edition: I didn’t really get virtualenvs until long after I started programming Python, though they’re now an essential part of my toolkit.
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Amazon Picking Challenge: Kiva Systems (where I interned in 2011) is setting up a robotics challenging for picking items off warehouse shelves. contexttimer 0.3.1: A handy Python context manger and decorator for timing things.
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Public Data Sets : Amazon Web Services: Amazon hosts a number of publicly datasets on AWS (including the common crawl corpus and the “Marvel Universe Social Graph”).
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The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets (No Excuses!)
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The pyspark documentation doesn’t include an example for the aggregateByKey RDD method.
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Hammock: A lightweight wrapper around the Python requests module to convert REST APIs into “dead simple programmatic APIs”.
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Philosophy of Statistics (Stanford Encyclopedia of Philosophy): I suspect that a lot of the Bayesian vs Frequentist debates ignore the important epistemological underpinnings of statistics.
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Open Sourcing a Python Project the Right Way: Great stuff that should be taught in school: “Most Python developers have written at least one tool, script, library or framework that others would find useful.
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Recently, I’ve spent a lot of time going back and forth between Python dicts and JSON.
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TIL how to checkout the last branch you were on in Git (before the current): git checkout - — Tim Hopper (@tdhopper) September 10, 2014
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textract: textract is a Python module and a command line tool for text extraction from many file formats.
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As I have noted before, body weight is a noisy thing.
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Ggplot2 To Ggvis: I’m a huge fan of ggplot2 for data visualization in R.
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How do I generate a uniform random integer partition?
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I spend a lot of time in IPython Notebooks for work.
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How can I pretty-print JSON at the command line?
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Arrow: better dates and times for Python: Arrow is a slick Python library “that offers a sensible, human-friendly approach to creating, manipulating, formatting and converting dates, times, and timestamps”.
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Back in July, I posted some analysis of my attempt at weight loss.
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I recently discovered the Twitter account @primes.
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I have largely moved from Textmate to Sublime Text 2 for text editing.
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Ralph Keyes, The Height of Your Life: I’ve heard this sort of thing repeatedly from tall men.
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I put on some weight during my time in grad school, and this spring, I decided to do something about it.
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I have started to realize that Monte Carlo methods of various kinds keep coming up in my work.
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I had the honor of being a technical reviewer for John Myles White’s outstanding book, “Bandit Algorithms for Website Optimization: Developing, Deploying, and Debugging.”
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I gave a talk at a recent Research Triangle Analysts meetup on scikit-learn, the excellent machine learning library for Python.
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I presented at INFORMS 2012 on Bringing Operations Research into the 21st Century with Online Video.
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I gave a talk at PyCarolinas 2012 about using Pickle and Redis to persist data with Python.
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For part of my sophomore year of college, I was a computer science major.
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Here are my notes on the derivation of the Least Squares Policy Iteration (LSPI) algorithm.
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I offered my calculus students bonus points to write a limerick or haiku on their final exam.
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I am teaching the dreaded calculus II this semester.
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Last month, Stephen Wolfram did a blog post on the Personal Analytics of his life.
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Yesterday, someone on MathOverflow asked Consider $n$ points generated randomly and uniformly on a unit square.
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Over the past 18 months, I’ve been slowly learning some machine learning.
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Stephen Wolfram, of Wolfram Research and Mathematica fame, did a Q&A (i.e.
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Although I was a computer science minor, I’d never heard of statistical machine learning until after college.
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As an undergraduate, our math department used Wolfram Research’s Mathematica heavily for instruction in a number of classes.
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I assume most people who are nerdy enough to read this blog are nerdy enough to know about the $\mathcal{P}$ vs $\mathcal{NP}$ problem1.
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In economics, some have asserted the efficient market hypothesis.
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In 1953, the eminent mathematician John Von Neumann (as they say, “Most mathematicians prove what they can, von Neumann proves what he wants”) wrote a letter to T.
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My friend John Cook asked me an interesting question recently: If you had a room full of people with a graduate degree in [operations research], what things would nearly everyone in the room know?
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A former grad school classmate of mine lived largely off of oatmeal and carrots.
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Notes from ISE 789, the healthcare-optimization seminar I am taking this term at NC State.