11 Practical Statements of Data Analytics

  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 ( or other forms of machine learning).
  4. In 90% of cases generalized linear regression will do the trick.
  5. Big Data is just a tool.
  6. You should embrace Bayesian approach.
  7. No one cares how you did it.
  8. Academia and business are two different worlds.
  9. Presentation is key – be the master of Powerpoint.
  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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