Here are the most popular posts in KDnuggets in October, based on the number of unique page views (UPV), and social share counts from Facebook, Twitter, and Addthis. Usually we limit the top post to those published in this month, but we saw a big jump in views in October for "9 Must-have skills you need to become a Data Scientist", which was published in May 2018, and felt it deserved to be included.

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

1. 9 Must-have skills you need to become a Data Scientist, updated, by Simplilearn (*)
2. 10 Best Mobile Apps for Data Scientist / Data Analysts, by Premjith Purushothaman (*)

 

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

3. How To Learn Data Science If You're Broke, by Harrison Jansma (*)
4. Graphs Are The Next Frontier In Data Science, by Reshama Shaikh

Most Viewed - Silver Badges (> 5,000 UPV)

5. Apache Spark Introduction for Beginners, by Vikash Kumar (*)
6. How to Create a Simple Neural Network in Python by Michael J. Garbade
7. The Main Approaches to Natural Language Processing Tasks, by Matthew Mayo
8. Top 8 Python Machine Learning Libraries, by Dan Clark (*)

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Most Shared - Silver Badges (>250 shares)

1. How To Learn Data Science If You're Broke, by Harrison Jansma
2. 10 Best Mobile Apps for Data Scientist / Data Analysts, by Premjith Purushothaman
3. The Main Approaches to Natural Language Processing Tasks, by Matthew Mayo
4. How to Create a Simple Neural Network in Python, by Michael J. Garbade
5. BIG, small or Right Data: Which is the proper focus?, by Ricardo Baeza-Yates
6. Graphs Are The Next Frontier In Data Science, by Reshama Shaikh

(*) 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. BIG, small or Right Data: Which is the proper focus?, by Ricardo Baeza-Yates
2. Using Confusion Matrices to Quantify the Cost of Being Wrong, by William Schmarzo
3. Basic Image Data Analysis Using Python - Part 4, by Mohammed Innat
4. Holy Grail of AI for Enterprise - Explainable AI, by Saurabh Kaushik
5. Implementing Automated Machine Learning Systems with Open Source Tools, by Matthew Mayo