The Inconvenient Truth About Data Science

Posted by Kamil Bartocha, a few excellent points. I agree with every single one of them:

  1. Data is never clean.
  2. You will spend most of your time cleaning and preparing data.
  3. 95% of tasks do not require deep learning.
  4. In 90% of cases generalized linear regression will do the trick.
  5. Big Data is just a tool.
  6. You should embrace the Bayesian approach.
  7. No one cares how you did it.
  8. Academia and business are two different worlds.
  9. Presentation is key – be a master of Power Point.
  10. All models are false, but some are useful.
  11. There is no fully automated Data Science. You need to get your hands dirty.
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2 thoughts on “The Inconvenient Truth About Data Science

  1. Hi,
    I am glad you like it! Great blog BTW. Drop me a line through email or Twitter – it would be great to chat.

    • Hi Kamil! Thank you. I’m long time follower of your work at marketingdistillery. Lot’s of interesting stuff! At twitter I’m rws@suboptimum. Thanks again and keep up the nice work!

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