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posted by LaminatorX on Sunday October 19 2014, @02:43AM   Printer-friendly
from the Mathamagician-of-Digitopolis dept.

Jim Edwards writes at Business Insider that Google is so large and has such a massive need for talent that if you have the right skills, Google is really enthusiastic to hear from you - especially if you know how to use MatLab, a fourth-generation programming language that allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. The key is that data is produced visually or graphically, rather than in a spreadsheet.

According to Jonathan Rosenberg, Google's former senior vice president for product management, being a master of statistics is probably your best way into Google right now and if you want to work at Google, make sure you can use MatLab. Big data — how to create it, manipulate it, and put it to good use — is one of those areas in which Google is really enthusiastic about. The sexy job in the next ten years will be statisticians. When every business has free and ubiquitous data, the ability to understand it and extract value from it becomes the complimentary scarce factor. It leads to intelligence, and the intelligent business is the successful business, regardless of its size. Rosenberg says that "My quote about statistics that I didn't use [last night] but often do is, 'Data is the sword of the 21st century, those who wield it [are] the samurai.'"

 
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  • (Score: 1) by novak on Sunday October 19 2014, @05:24AM

    by novak (4683) on Sunday October 19 2014, @05:24AM (#107497) Homepage

    Matlab's math libraries are not better than any other math libraries, especially not without paying for several toolkits.

    Also it's worth pointing out that speed is the point of anything being used to analyze non-trivial data sets. Do a power weighted reverse interpolation onto an arbitrary mesh for a real data set (well, the software I wrote was working on data sets in the 10 GB size range (dp), being mapped onto 100 MB meshes (dp)). If speed doesn't matter yet it soon will.

    Ooh, here's a fun bit of info: you'll take a major speed hit in matlab on that interpolation if you use any power besides 2.

    Math is not a side bar to 'real' programming, some of the highest performance software is math software, and some of the hardest problems are math problems. Navier-Stokes was the big one in the field I worked. If you could do 100 times as many computations per second as 10 years back, customers expect 100 times as many computations.

    I don't really know about Octave, I tried to use it once or twice and was not really impressed. I recall one matlab program seemed to not run but it turned out it was just running really slow. That was probably five years back though, it may have improved.

    --
    novak
  • (Score: 2) by kaszz on Sunday October 19 2014, @05:33AM

    by kaszz (4211) on Sunday October 19 2014, @05:33AM (#107501) Journal

    I was thinking of stuff like FFT or image recognition etc. Small dataset but complicated math.

    • (Score: 1) by novak on Sunday October 19 2014, @05:46AM

      by novak (4683) on Sunday October 19 2014, @05:46AM (#107502) Homepage

      That's probably the closest you can get to something matlab works well for. If you buy the FFT toolkit or image processing toolkit instead of using a free library in another language.

      --
      novak