Top July Stories: Cartoon: Data Scientist was the sexiest job of the 21st century until …; Does PCA really improve classification outcome? Causation in a nutshell

Here are the most popular posts in KDnuggets in July, based on the number of unique page views (UPV), the remaining social share counts from Facebook, Twitter, and Addthis.

Most Viewed - Platinum Badge (>24,000 UPV)

1. Cartoon: Data Scientist was the sexiest job of the 21st century until ..., by Gregory Piatetsky (*)

 

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

2. 5 of Our Favorite Free Visualization Tools, by Richard Vermillion
3. SQL Cheat Sheet, by Dan Clark (*)

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

4. Text Mining on the Command Line, by Sabber Ahamed
5. Dimensionality Reduction: Does PCA really improve classification outcome?, by Meigarom Diego Fernandes
6. How to Build a Data Science Portfolio, by Michael Galarnyk (*)

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Most Shared - Gold Badges (>600 shares)

1. Dimensionality Reduction: Does PCA really improve classification outcome?, by Meigarom Diego Fernandes (*)

Most Shared - Silver Badges (>300 shares)

2. Comparison of Top 6 Python NLP Libraries, by ActiveWizards
3. Analyze a Soccer (Football) Game Using Tensorflow Object Detection and OpenCV, by Priyanka Kochhar
4. Causation in a Nutshell, by Kevin Gray
5. 5 Quick and Easy Data Visualizations in Python with Code, by George Seif (*)
6. Automated Machine Learning vs Automated Data Science, by Matthew Mayo
7. SQL Cheat Sheet, by Dan Clark
8. 5 of Our Favorite Free Visualization Tools, by Richard Vermillion
9. Genetic Algorithm Implementation in Python, by Ahmed Gad
10. Explaining the 68-95-99.7 rule for a Normal Distribution, by Michael Galarnyk (*)

(*) 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. Causation in a Nutshell, by Kevin Gray
2. Efficient Graph-based Word Sense Induction, by UMass Amherst graduate students Haw-Shiuan Chang, Amol Agrawal, Ananya Ganesh, Anirudha Desai and Vinayak Mathur; Andrew McCallum, Professor and Director of the Center for Data Science at UMass Amherst; and Alfred Hough, Lead AI Researcher at Lexalytics
3. 9 Reasons why your machine learning project will fail, by Alberto Artasanchez
4. The 4 Levels of Data Usage in Data Science, by Matthew Mayo
5. The ultimate list of Web Scraping tools and software, by Ida Jessie Sagina
6. Comparison of Top 6 Python NLP Libraries, by ActiveWizards