Top all-time · #1966
John Myles White
Personal blog · johnmyleswhite.comdatamathprogramming
John Myles White's personal blog at johnmyleswhite.com covers data, math and programming. Since 2010, 40 different Hacker News readers have linked it 46 times, most often “Modes, Medians and Means: A Unifying Perspective”. The last post was in 2020, but the archive is still widely read.
John Myles White's personal website
Most-linked posts?
- Modes, Medians and Means: A Unifying Perspective7 people · 7 mentions · first linked 2013-03-23
- Using Norms to Understand Linear Regression4 people · 4 mentions · first linked 2017-02-01
- The Relationship between Vectorized and Devectorized Code3 people · 3 mentions · first linked 2013-12-22
- Why does factorial(21) equal -4249290049419214848?2 people · 2 mentions · first linked 2013-02-28
- The Lesser Known Normal Forms of Database Design2 people · 2 mentions · first linked 2014-09-11
- Julia, I love you (2012)2 people · 2 mentions · first linked 2012-04-16
What Hacker News says?
Your followup post ( http://www.johnmyleswhite.com/notebook/2013/03/22/using-norm... ) is excellent. Thank you!
Comment linking /notebook/2013/03/22/using-norms-to-understand-linear-regression/
on “Unlearning descriptive statistics”Submitted Modes, Medians and Means: A Unifying Perspective as a story · 332 points
HN discussionFor readers who are OK with some math, I recommend John Myles White's eye-opening post about means, medians, and modes: http://www.johnmyleswhite.com/notebook/2013/03/22/modes-medi... He describes these summary descriptive stats in terms of what penalty function they minimize: mean minimizes L2, median minimizes L1, mode minimizes L0. A single-number statistic is _going_ to leave things out, so if you must boil thin…
Comment linking /notebook/2013/03/22/modes-medians-and-means-an-unifying-perspective/
on “Unlearning descriptive statistics”Submitted Modes, Medians and Means: A Unifying Perspective (2013) as a story · 141 points
HN discussionThere is a follow up post [0] talking about L_p norms, although it doesn't mention L_infinity [0]: http://www.johnmyleswhite.com/notebook/2013/03/22/using-norm...
Comment linking /notebook/2013/03/22/using-norms-to-understand-linear-regression/
on “Modes, Medians and Means: A Unifying Perspective”Submitted Julia, I love you (2012) as a story · 136 points
HN discussionIn case anyone wants to dig into the follow up on Lp norms, here it is: http://www.johnmyleswhite.com/notebook/2013/03/22/using-norm...
Comment linking /notebook/2013/03/22/using-norms-to-understand-linear-regression/
on “Modes, Medians and Means: A Unifying Perspective”Submitted What's wrong with statistics in Julia? as a story · 132 points
HN discussionOkay. This post: http://www.johnmyleswhite.com/notebook/2013/12/22/the-relati... had worried me a couple of years ago. JMW shows that vectorized was much slower also in Julia (though still both faster than R - but that's not difficult). Glad to see Julia is very fast in both cases, though it's still somewhat perplexing the extent to which vectorized code is necessarily slower. I'm thinking that the future of GPU ena…
Comment linking /notebook/2013/12/22/the-relationship-between-vectorized-and-devectorized-code/
on “Comparison – R vs. Python: head to head data analysis”Submitted My Experience at JuliaCon as a story · 114 points
HN discussionIt seems that though with in Julia, vectorized code is typically slower than non-vectorized, it is still faster than in R [1] / Python [2]. [1] http://www.johnmyleswhite.com/notebook/2013/12/22/the-relati... [2] http://blog.rawrjustin.com/blog/2014/03/18/julia-vs-python-m...
Comment linking /notebook/2013/12/22/the-relationship-between-vectorized-and-devectorized-code/
on “Comparison – R vs. Python: head to head data analysis”Submitted Why I’m Not a Fan of R-Squared as a story · 77 points
HN discussionSeems like as time goes on, I have to deal with more and more bugs in iOS and OS X. I know I'm not the only one.[1] I think I've figured out why: Apple doesn't track bugs. I just know they don't, even though I don't work there. Its like they just add features and release a new version, so they can ignore all bugs reported for previous versions. Crash reports are automatically and constantly submitted (looking at you…
Comment linking /notebook/2012/10/02/finder-bug-in-os-x/
on “Remember when people tracked bugs?”Submitted The State of Statistics in Julia as a story · 69 points
HN discussionI disagree with the assertion (it is unsourced on wikipedia) -- colloquially the average is the arithmetic average, not a median or mode. At a next level up, average typically refers to - Arithmetic mean - Geometric mean (exp of average of log values) - Harmonic mean Mode and medians are measures of centrality, true, but are not equivalent to the arithmetic mean. Fun fact (h/t John Myles White) the arithmetic mean,…
Comment linking /notebook/2013/03/22/modes-medians-and-means-an-unifying-perspective/
on “SF restaurants are suffocating”Submitted Why Julia's DataFrames Are Still Slow as a story · 60 points
HN discussionYou might like this blog post from John Myles White: http://www.johnmyleswhite.com/notebook/2013/03/22/modes-medi... It compares mode, median, and mean as each being specific implementations of a more general concept of discrepancy.
Comment linking /notebook/2013/03/22/modes-medians-and-means-an-unifying-perspective/
on “Azure Functions vs. AWS Lambda – Scaling Face Off”Submitted The Social Dynamics of the R Core Team as a story · 24 points
HN discussionI think people often underestimate (or just plain don't know about) the degree to which a multiple-dispatch-based programming language like Julia effectively implies its whole own dispatch-oriented programming paradigm, with both some amazing advantages (composability [1], and an IMO excellent balance of speed and interactivity when combined with JAOT compilation), but also some entirely new pitfalls to watch out fo…
Comment linking /notebook/2013/12/06/writing-type-stable-code-in-julia/
on “Opticsim.jl: Optical Simulation Software”Submitted Writing Type-Stable Code in Julia as a story · 5 points
HN discussionJulia supports arbitrary precision arithmetic just fine, but you need to explicitly use it. Overflow checks don't matter in Python or Ruby where everything is relatively slow. See also: http://www.johnmyleswhite.com/notebook/2013/01/03/computers-...
Comment linking /notebook/2013/01/03/computers-are-machines/
on “Try Julia”Submitted Hopfield Networks in Julia as a story · 5 points
HN discussion> So who knows, maybe the power of lisp combined with a non-lispy syntax is a balloon that can fly. Sounds like Apple's old language Dylan, and perhaps the Julia language: http://www.johnmyleswhite.com/notebook/2012/03/31/julia-i-lo...
Comment linking /notebook/2012/03/31/julia-i-love-you/
on “A Lisp based programming language I'm creating”Submitted How I learned to make decisions and love causation as a story · 5 points
HN discussionI have extensive work in Matlab, C, Fortran, R, Python, Julia, SAS (IML), and am learning Go and Rust. I have played with Java and Kotlin on non-serious projects. I typically use Python for data-related tasks. Julia is just okay. It lost its steam due to long beta, slow time to first plot after 1.0 release, and generally not being a strategically adopted language by ML innovation groups. A great example of what is v…
Comment linking /about/
on “JDF.jl – Julia DataFrames serialization format”Submitted Writing Better Statistical Programs in R as a story · 4 points
HN discussionSubmitted Comparing Julia and R’s Vocabularies as a story · 4 points
HN discussionSubmitted The Psychology of Music and the 'tuneR' Package as a story · 4 points
HN discussionSubmitted Modes, Medians and Means: A Unifying Perspective as a story · 3 points
HN discussionSubmitted Why does factorial(21) equal -4249290049419214848? as a story · 3 points
HN discussion
