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Top November Stories: The 10 Statistical Techniques Data Scientists Need to Master


Also: Best Online Masters in Data Science and Analytics - a comprehensive, unbiased survey; Deep Learning Specialization by Andrew Ng - 21 Lessons Learned; Machine Learning Algorithms: Which One to Choose for Your Problem; Want to know how Deep Learning works? Here's a quick guide



For the month of November, we also recognize the most popular posts and blogger based on unique page views (UPV) and social shares.

Platinum BlogMost Viewed - Platinum Badge
(>24,000 views)

  1. The 10 Statistical Techniques Data Scientists Need to Master, by James Le (*)



 

Gold BlogMost Viewed - Gold Badges (>12,000 UPV)

  1. Best Online Masters in Data Science and Analytics - a comprehensive, unbiased survey, by Gregory Piatetsky
  2. Deep Learning Specialization by Andrew Ng - 21 Lessons Learned, by Ryan Shrott
  3. Advice For New and Junior Data Scientists, by Robert Chang (*)
  4. When Will Demand for Data Scientists/Machine Learning Experts Peak?, by Gregory Piatetsky (*)


Silver BlogMost Viewed - Silver Badges (> 6,000 UPV)

  1. A Day in the Life of a Data Scientist, by Matthew Mayo (*)
  2. Top 10 Videos on Deep Learning in Python, by Reena Shaw (*)
  3. Machine Learning Algorithms: Which One to Choose for Your Problem, by Daniil Korbut
  4. Interpreting Machine Learning Models: An Overview, by Matthew Mayo
  5. Did Spark Really Kill Hadoop?, by Julia Cook (*)



Gold BlogMost Shared - Gold Badges (>1,200 shares)

  1. Machine Learning Algorithms: Which One to Choose for Your Problem, by Daniil Korbut
  2. Want to know how Deep Learning works? Here's a quick guide for everyone, by Radu Raicea (*)
  3. Interpreting Machine Learning Models: An Overview, by Matthew Mayo
  4. Deep Learning Specialization by Andrew Ng - 21 Lessons Learned, by Ryan Shrott


Silver BlogMost Shared - Silver Badges (>700 shares)

  1. Top 10 Videos on Deep Learning in Python, by Reena Shaw
  2. Advice For New and Junior Data Scientists, by Robert Chang
  3. A Framework for Approaching Textual Data Science Tasks, by Matthew Mayo
  4. When Will Demand for Data Scientists/Machine Learning Experts Peak?, by Gregory Piatetsky
  5. Why You Should Forget "for-loop" for Data Science Code and Embrace Vectorization, by Tirthajyoti Sarkar
  6. A Day in the Life of a Data Scientist, by Matthew Mayo
  7. Understanding Deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras, by Ahmed Besbes
  8. Best Online Masters in Data Science and Analytics - a comprehensive, unbiased survey, by Gregory Piatetsky
  9. Automated Feature Engineering for Time Series Data, by Michael Schmidt (*)


(*) indicates that badge added or upgraded based on these monthly results.

Most Shareable (Viral) Blogs

Among the top blogs, here are the 5 blogs with the highest ratio of shares/unique views, which suggests that people who read it really liked it.
  1. How (and Why) to Create a Good Validation Set, by Rachel Thomas
  2. Estimating an Optimal Learning Rate For a Deep Neural Network, by Pavel Surmenok
  3. PySpark SQL Cheat Sheet: Big Data in Python, by Karlijn Willems
  4. Understanding Deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras, by Ahmed Besbes
  5. Blockchain Key Terms, Explained, by Reena Shaw