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Vincent's selection for the last 30 days. Enjoy the reading, share with colleagues!

  1. Big Data: Making Complex Things Simpler
  2. Setting up a Data Science Laboratory
  3. 66 job interview questions for data scientists
  4. Re-identifying anonymous people with big data
  5. Excerpt from Too Big to Ignore
  6. Innumeracy: How Your Pricing Strategy can take Advantage of Mathema...
  7. An HR Algorithm to Evaluate Job Candidates–With or Without a Resume
  8. Fake data science
  9. Analytics{Benzene} => {big Pharma, Nanotechnologies}
  10. The graveyard of programming languages
  11. Beware the Big Errors of ‘Big Data’
  12. 53.5 billion clicks dataset available for benchmarking and testing
  13. Predicting the chance that your tax return will be audited
  14. What the Intelligence Community Is Doing With Big Data
  15. Data Monetization: A Road Paved On Top Of Data Sets
  16. IBM Security Tool Can Flag ‘Disgruntled Employees’
  17. Six Types Of Analyses Every Data Scientist Should Know
  18. Is Your College Going Out of Business?
  19. Big data and the death of the theorist
  20. Crowdcharting, anyone?
  21. IBM, Universities Team Up To Build Data Scientists
  22. Data Science: Buyer Beware
  23. The jobs numbers have been terrific lately. Can we believe them?
  24. To Avoid Nasty Surprises, Higher Ed Turns To Prediction
  25. 11 Steps To Finding Data Scientists
  26. What Separates a Good Data Scientist from a Great One
  27. Six Types Of Analyses Every Data Scientist Should Know
  28. Statisticians’ Place in Big Data
  29. As Startups Produce More Data, the Search for Data Scientists Grows...
  30. The top ten worst graphs

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