Top-19 articles of 2019

Top-19 articles of 2019

With only one day remaining in 2019, let’s review the year. 2019 was my third year of blogging and it went by even quicker than the previous two!

Personally, it has been a busy year for me: I started a new job, increased my speaking and teaching activities, bought and moved to my new house, and got married op top of that!

Fortunately, I also started working parttime. This way, I could still reserve some time for learning and sharing my learnings. And sharing I did:

I posted 95 blogs in 2019!
That means one new post every 4 days!

paulvanderlaken.com improved its online footprint as well. We received over 100k visitors in 2019! And many of you subscribed and sticked around. Our little community now includes 55 more members than it did last year! And that is not even including the followers to my new twitter bot Artificial Stupidity!

Thank you for your continued interest!

Join 234 other followers

Now, I am always curious as to what brings you to my website, so let’s have a look at some 2019 statistics (which I downloaded via my new Python scraper).

Most read articles

There is clearly a power distribution in the quantity with which you read my blogs.

Some blogs consistently attract dozens of visitors each day. Others have only handful of visitors over the course of a year.

These are the 19 articles which were most read in 2019. Hyperlinks are included below the bar chart. It’s a nice combination of R programming, machine learning, HR-related materials, and some entertainment (games & gambling) in between.

Which have and haven’t you read?

  1. R resources
  2. R tips and tricks
  3. New to R?
  4. Books for the modern, data-driven HR professional
  5. The house always wins
  6. Visualization innovations
  7. Simple correlation analysis in R
  8. Beating battleships with algorithms and AI
  9. Regular expressions in R
  10. Simpson’s paradox
  11. Visualizing the k-means clustering algorithm
  12. Survival of the best fit
  13. Datasets to practice and learn data science
  14. Identifying dirty twitter bots
  15. Game of Thrones map
  16. Screeps
  17. Northstar
  18. The difference between DS, ML, and AI visualized
  19. Light GBM vs. XGBoost

Rising stars

Half of these most read articles have actually been published in 2017 or ’18 already. However, of the 95 articles published in 2019, some also demonstrate promising visitor patterns:

The People Analytics books, Visual innovations, and AI Battleships are in the top 19, and several others made it too.

Some of these newer blogs haven’t had the time to mature and redeem their place yet though. Regardless, I have high hopes!

Particularly for Neural Synesthesia, which was easily one of my greatest WOW-moments for ML applications in 2019. It’s truly mesmerizing to see a GAN traverse its latent space.

Reading & posting patterns

I have been posting quite regularly throughout the year. Apart from a holiday to Thailand during the start of January, and the start of my new job in February.

While I write and post most of my blogs in the weekend, I guess I should consider postponing publishing. As you guys are mostly active during Tuesdays and Wedsnesdays!

Statistical summary of 2019

What better way to end 2019 than with a statistical summary?

I have posted more and shorter blogs, and you’ve rewarded me with visits and more likes (also per post). However, we need more discussion!

Statistic2018 2019 Δ
Views85614107388+25%
Unique visitors5759470615+23%
Posts6195+56%
Words / post518371-40%
Likes51111118%
Comments2416-33%
As of 29/12/2019

2020 Outlook

It took some time to get started, but halfway 2017 my blog started attracting an audience. People stayed on during 2018, and visitor number continued to increase through 2019.

With an ongoing expansion from R into Python, and an increased focus on sharing resources, applications, and novelties related to data visualization and machine learning, I have a lot more in store for 2020!

I hope you stick around for the ride!

Please like, subscribe, share, and comment, and we’ll make sure 2020 will be at least as interesting and full of (machine) learning as 2019 has been!

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