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

Platinum Blog
Most Viewed - Platinum Badge
(>24,000 views)

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



 

Gold Blog
Most 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 Blog
Most 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 Blog
Most 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 Blog
Most 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