How come everyone is AI, ML and DS experts on LinkedIn feeds

PayPal sarcasm
Jun 7 10 Comments

Question says it all. Every Tom, Dick and Harry is AI, ML engineer and Data Scientists.

Folks who are really working on these stuff. Do you get to work on Maths and Statistics part of them or just another "use that library, sir" thingy?

I would like to know precisely what is your responsibility in your daily work?

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TOP 10 Comments
  • Twitch jkley28
    when every job requires a decade of experience in react and tensorflow, expect people to claim bullshit capabilities
    Jun 7 0
  • Microsoft L61
    They will claim expertise on something g else in next 3-5 years
    Jun 7 0
  • Facebook / Retail bookfacer
    People put this stuff on their linked in because it is in demand. Not rocket science.
    Jun 7 1
    • PayPal sarcasm
      OP
      Do you work on these? Can you elaborate your job responsibilities?
      Jun 7
  • Walgreens StefanoP
    ^ exactly

    To compare to software engineering,

    When you build software, it isn't over when you just import a library and tweak the sample applications (this is what happens when some "data scientists" approach a problem. But they shouldn't choose their framework before knowing of the problem to be solved)

    After you choose your software stack, now you need to actually go write the code for your particular application (in data science land, this means understanding your data through analysis, learning about the domain of the problem, etc., and verifying your solution actually solves the given problem)

    So it's sort of inverse to software engineering, but the core is the analysis beforehand, solution/choosing algorithms and approach to learn from the data, and analysis afterward.
    Jun 7 1
    • Walgreens StefanoP
      Fuck this was supposed to be a comment reply. Oh well
      Jun 7
  • Microsoft Vbsm66
    There's no established minimum bar for putting that on your LinkedIn
    Jun 7 0
  • Walgreens StefanoP
    You get into the math and statistics or you're not doing true data science
    Jun 7 2
    • Daimler yrcair52s
      could you elaborate on this?
      Jun 7
    • Tweaking existing ml algorithm and/or creating new ml algorithm to fit a business need vs let me shotgun all the existing ml algorithm into this “big data” and see what comes out
      Jun 7