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Top November Stories: Trump, Failure of Prediction, and Lessons for Data Scientists


Also: How Bayesian Inference Works; Top 20 Python Machine Learning Open Source Projects, updated; Machine Learning vs Statistics



Most Viewed

  1. Clinton vs Trump, Upshot forecast Trump, Failure of Prediction, and Lessons for Data Scientists, by Gregory Piatetsky
  2. How Bayesian Inference Works, by Brandon Rohrer
  3. Top 20 Python Machine Learning Open Source Projects, updated, by Prasad Pore
  4. Top 10 Amazon Books in Data Mining, 2016 Edition, by Matthew Mayo
  5. Learn Data Science for Excellence and not just for the Exams
  6. An Intuitive Explanation of Convolutional Neural Networks
  7. Data Science 101: How to get good at R
  8. Eight Things an R user Will Find Frustrating When Trying to Learn Python
  9. Tips for Beginner Machine Learning/Data Scientists Feeling Overwhelmed
  10. Combining Different Methods to Create Advanced Time Series Prediction


Most Shared

  1. Trump, Failure of Prediction, and Lessons for Data Scientists, by Gregory Piatetsky
  2. Data ScienceLearn Data Science for Excellence and not just for the Exams, by Prasad Pore
  3. How Bayesian Inference Works, by Brandon Rohrer
  4. Machine Learning vs Statistics, by Aatash Shah
  5. Top 10 Amazon Books in Data Mining, 2016 Edition
  6. Top 20 Python Machine Learning Open Source Projects, updated
  7. Continuous improvement for IoT through AI / Continuous learning
  8. Data Science and Big Data, Explained
  9. Data Science Basics: An Introduction to Ensemble Learners
  10. Combining Different Methods to Create Advanced Time Series Prediction