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Previously on "Any Data analysts/scientists out there"

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  • vetran
    replied
    Originally posted by eek View Post
    your continual posting throws your second statement into doubt.
    the wife has told him he has to put the toys he littered on the lounge floor away, her mom is coming round to sleep on the sofa. If he doesn't do it by the time she comes off shift he won't get a choccy biccy.

    Leave a comment:


  • DimPrawn
    replied
    Yes it's an interesting area (to me anyway).

    This blog post describes in detail what you need to know and do to call yourself a data scientist.

    No, Really, Some of My Best Friends Are Data Scientists

    Leave a comment:


  • d000hg
    replied
    Another potentially interesting thread ruined. Keep it in your pants Sas, plenty of other threads better suited to I'll see you there!

    Leave a comment:


  • eek
    replied
    Originally posted by sasguru View Post
    You come across as a real loser. Keep furiously if you think it helps.
    I've got some work to do.
    While I agree with your first statement, your continual posting throws your second statement into doubt.

    Leave a comment:


  • sasguru
    replied
    Originally posted by aussielong View Post
    Stats is for those that couldn't cut it at pure maths.

    Quant beats stato. Certainly in terms of pay, prestige, employability, etc. Oh but hang on, Data Science is the next big thing, right? Vauxhall conference loser thinks he's premiership.
    You come across as a real loser. Keep furiously if you think it helps.
    I've got some work to do.

    Leave a comment:


  • aussielong
    replied
    Originally posted by sasguru View Post
    Thanks for showing the depth of your misunderstanding.
    Stats is epistemological and hence touches on philosophy, accountancy is merely counting.
    Keep digging though, you make me laugh.
    Stats is for those that couldn't cut it at pure maths.

    Quant beats stato. Certainly in terms of pay, prestige, employability, etc. Oh but hang on, Data Science is the next big thing, right? Vauxhall conference loser thinks he's premiership.

    Leave a comment:


  • sasguru
    replied
    Originally posted by DimPrawn View Post
    And what did Bob find?



    I think what that article shows is what I have long suspected: Bob, on average, isn't very good at all, hence all the cheating.
    Of course in a population of 1 billion, there are bound to be some very good people, simply by chance, but in general Bob's education, creativity and ability to do the job is poor.
    Those of you who have been bobbed should consider that is because you're poor too.

    Leave a comment:


  • DimPrawn
    replied
    And what did Bob find?

    Bhattacharji works as a data scientist with HackerRank, a social platform for coders. But he has also put his skills to good use on another task — he managed to scrape the 2012 and 2013 exam results of almost a million students from the two central boards in India, the CBSE and ICSE.

    Through this experiment, he found something unusual — the scoring patterns were irregular, which meant that score manipulation and inflation were rampant in these boards.

    Leave a comment:


  • DimPrawn
    replied
    What's a Data Scientist?

    Ask Bob.

    What exactly do data scientists do? - Lifestyle - DNA

    Plenty cheapness. Much spreadsheets.

    Leave a comment:


  • sasguru
    replied
    Originally posted by aussielong View Post
    Why did the statistician become a statistician? He found accountancy too exciting.
    Thanks for showing the depth of your misunderstanding.
    Stats is epistemological and hence touches on philosophy, accountancy is merely counting.
    Keep digging though, you make me laugh.

    Leave a comment:


  • aussielong
    replied
    Originally posted by sasguru View Post
    In the data science/statistical learning arena, for the sake of argument there are 2 approaches: the statistical and what statisticians refer to (usually wrongly) as the CS approach: the latter consisting of algorithms that produce results like clustering but are very ad-hoc: a good example is k-means.*
    Statos are suspicious of the latter, CS people say "if it works
    Why did the statistician become a statistician? He found accountancy too exciting.

    Leave a comment:


  • sasguru
    replied
    Originally posted by Spacecadet View Post
    I posted this on here a couple of weeks ago:
    Becoming a Data Scientist - Curriculum via Metromap ← Pragmatic Perspectives!

    Problem with the whole data science/big data thing is that it is about to hit the top of the hype cycle:
    Hype cycle - Wikipedia, the free encyclopedia

    If that model is correct then it will take 2 years to get back to normal
    True - although I think the its well and truly in the hype cycle already . I know people who have "big data" and "data scientist" on their CV. To me that's BS. Either you have fantastic data-munging skills or stats skills or both.

    Leave a comment:


  • Spacecadet
    replied
    Originally posted by DodgyAgent View Post
    I am looking to set up a speciality business placing contract data analysts.
    Are any of you knowledgeable enough to help me:
    1. Find data analysts to place
    2. Understand the key attributes of a good data analyst
    3. Understand where in organisations these people sit
    4. Who to talk to in organisations about requirements (please god not HR/internal recruitment)
    Or is this a bit off topic for CUK?
    I posted this on here a couple of weeks ago:
    Becoming a Data Scientist - Curriculum via Metromap ← Pragmatic Perspectives!

    Problem with the whole data science/big data thing is that it is about to hit the top of the hype cycle:
    Hype cycle - Wikipedia, the free encyclopedia

    If that model is correct then it will take 2 years to get back to normal

    Leave a comment:


  • bobspud
    replied
    Originally posted by BigRed View Post
    I thought the software did all the data mining these days instead of having to hire sasguru to do all the brain numbing number crunching?
    Mining data is not a problem. But reading it and making the connections is. If you want a good analogy try using Splunk log aggregation indexing. Even with just a 100 or so log devices you can generate several thousand traps in an hour.

    I can look at a report and give you a pointer where to look for the problem in a matter of a few minutes but it still needs that human eye to spot the notional "this does not look like it should" I have no doubt that one day I will be replaceable for an AI unit that is less petulant.

    Leave a comment:


  • Mich the Tester
    replied
    Originally posted by sasguru View Post
    If that were the case you could expect constant chaos - contrary to popular impression and sensational articles real AI does not exist yet.
    I've seen a lot of AS in my time though.

    Leave a comment:

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