Here are the most popular posts in KDnuggets in May, based on the number of unique page views (UPV), and social share counts from Facebook, Twitter, and Addthis.
Most Viewed - Gold Badges (>12,000 UPV)
- 5 Useful Statistics Data Scientists Need to Know, by George Seif
- 7 Steps to Mastering Intermediate Machine Learning with Python - 2019 Edition, by Matthew Mayo
- Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS, by Bob Muenchen
- If you're a developer transitioning into data science, here are your best resources, by Cecilia Shao
Most Viewed - Silver Badges (> 6,000 UPV)
- How to choose a visualization, by Steven Franconeri
- How to Learn Python for Data Science the Right Way, by Manu Jeevan
- Understanding Cloud Data Services, by Charlie Crocker
- Top 10 Statistics Mistakes Made by Data Scientists, by Norman Niemer (*)
- PyViz: Simplifying the Data Visualisation Process in Python, by Parul Pandey (*)
- Random Forest vs Neural Networks: Which is Better, and When?, by Piotr Plonski (*)
- Spark NLP: Getting Started With The World's Most Widely Used NLP Library In The Enterprise, by David Talby
- Math for Programmers. Manning (*)
- The Infinity Stones of Data Science, by Matthew Mayo (*)
- 7 Steps to Mastering Data Preparation for Machine Learning with Python - 2019 Edition, by Matthew Mayo
Most Shared - Gold Badges (>600 shares)
- Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS, by Bob Muenchen
- 5 Useful Statistics Data Scientists Need to Know, by George Seif
- How to Learn Python for Data Science the Right Way, by Manu Jeevan (*)
- 7 Steps to Mastering Intermediate Machine Learning with Python - 2019 Edition, by Matthew Mayo
- How to choose a visualization, by Steven Franconeri (*)
Most Shared - Silver Badges (>300 shares)
- 7 Steps to Mastering Data Preparation for Machine Learning with Python - 2019 Edition, by Matthew Mayo
- Top 10 Statistics Mistakes Made by Data Scientists, by Norman Niemer
- Random Forest vs Neural Networks: Which is Better, and When?, by Piotr Plonski
- Jupyter Notebooks: Data Science Reporting, by Asel Mendis
- NLP and Computer Vision Integrated, by Sciforce (*)
- Understanding Cloud Data Services, by Charlie Crocker
- The Machine Learning Puzzle, Explained, by Matthew Mayo
- What you need to know: The Modern Open-Source Data Science/Machine Learning Ecosystem, by Gregory Piatetsky
(*) indicates that badge added or upgraded based on these monthly results.
Most Shareable (Viral) Blogs
Among the top blogs, here are the blogs with the highest ratio of shares/unique views, which suggests that people who read it really liked it.
- Ten random useful things in R that you might not know about, by Keith McNulty
- How To Get Funding For AI Startups, by Alexandre Gonfalonieri
- Jupyter Notebooks: Data Science Reporting, by Asel Mendis
- NLP and Computer Vision, by Integrated Sciforce
- Evolving Deep Neural Networks, by Luis Da Silva
- 7 Steps to Mastering Data Preparation for Machine Learning with Python - 2019 Edition, by Matthew Mayo