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

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

1. Data Visualization Cheat Sheet, by Jon Schwabish
2. Eight iconic examples of data visualisation, by James Cook University Online
3. Data Scientist guide for getting started with Docker, by Dan Clark

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

4. Basic Statistics in Python: Descriptive Statistics, by Christian Pascual
5. Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code, by Favio Vazquez
6. Top 10 roles in AI and data science, by Cassie Kozyrkov (*)
7. Data Scientist Interviews Demystified, by Colleen M. Farrelly
8. Programming Best Practices For Data Science, by Srini Kadamati (*)

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Most Shared - Gold Badges (>600 shares)

1. Data Visualization Cheat Sheet, by Jon Schwabish
2. Basic Statistics in Python: Descriptive Statistics, by Christian Pascual

Most Shared - Silver Badges (>300 shares)

3. Data Scientist guide for getting started with Docker, by Dan Clark
4. AI Knowledge Map: How To Classify AI Technologies, by Francesco Corea
5. Eight iconic examples of data visualisation, by James Cook University Online
6. Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code, by Favio Vazquez
7. From Data to Viz: how to select the the right chart for your data, by Yan Holtz
8. Top 10 roles in AI and data science, by Cassie Kozyrkov (*)
9. Understanding Language Syntax and Structure: A Practitioner's Guide to NLP, by Dipanjan Sarkar (*)
10. GitHub Python Data Science Spotlight: AutoML, NLP, Visualization, ML Workflows, by Matthew Mayo
11. Topic Modeling with LSA, PLSA, LDA & lda2Vec, by Joyce Xu
12. Unveiling Mathematics Behind XGBoost, by Ajit Samudrala (*)

(*) 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. From Data to Viz: how to select the the right chart for your data, by Yan Holtz
2. AI Knowledge Map: How To Classify AI Technologies, by Francesco Corea
3. Introduction to Fraud Detection Systems, by Miguel Gonzalez-Fierro
4. Project Hydrogen, new initiative based on Apache Spark to support AI and Data Science, by Reynold Xin
5. Comparison of the Most Useful Text Processing APIs, by Active Wizards
6. Understanding Language Syntax and Structure: A Practitioner's Guide to NLP, by Dipanjan Sarkar