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Top Stories, Mar 11-17: Who is a typical Data Scientist in 2019?; The Pareto Principle for Data Scientists


Also: Another 10 Free Must-Read Books for Machine Learning and Data Science; Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision; My favorite mind-blowing Machine Learning/AI breakthroughs; The 7 Myths of Data Anonymisation



Most Popular Last Week

  1. new Typical Who is a typical Data Scientist in 2019?, by Iliya Valchanov
  2. new The Pareto Principle for Data Scientists, by Pradeep Gulipalli
  3. new Another 10 Free Must-Read Books for Machine Learning and Data Science
  4. new My favorite mind-blowing Machine Learning/AI breakthroughs
  5. decrease 9 Must-have skills you need to become a Data Scientist, updated
  6. new Top R Packages for Data Cleaning
  7. new Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision

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  1. Who is a typical Data Scientist in 2019?, by Iliya Valchanov - Mar 11, 2019.
  2. Pareto The Pareto Principle for Data Scientists, by Pradeep Gulipalli - Mar 11, 2019.
  3. Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision - Mar 15, 2019.
  4. My favorite mind-blowing Machine Learning/AI breakthroughs - Mar 14, 2019.
  5. The 7 Myths of Data Anonymisation - Mar 12, 2019.
  6. Top R Packages for Data Cleaning - Mar 15, 2019.
  7. Securing your future in big data - Mar 12, 2019.

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  5. decrease Gainers, Losers, and Trends in Gartner 2019 Magic Quadrant for Data Science and Machine Learning Platforms
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Most Shared Past 30 Days

  1. Artificial Neural Network Implementation using NumPy and Image Classification - Feb 21, 2019.
  2. Another 10 Free Must-Read Books for Machine Learning and Data Science - Mar 06, 2019.
  3. How to Setup a Python Environment for Machine Learning - Feb 18, 2019.
  4. 19 Inspiring Women in AI, Big Data, Data Science, Machine Learning - Mar 08, 2019.
  5. Who is a typical Data Scientist in 2019? - Mar 11, 2019.
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  7. The Pareto Principle for Data Scientists - Mar 11, 2019.

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