KDnuggets now a secure site, change in FB counts, and our most liked content
KDnuggets has recently converted to a secure https access which reset our facebook "like" counts. However, we saved the data - see which pages were most liked.
Security on the web is very important, especially for sites that store your personal information.
However, even sites that don't store sensitive information are moving from http: to https: (secure access), especially since Google announced that they will start showing
insecure warning in Google Chrome as of October 2017.
Although KDnuggets is not storing your personal information, we also moved to https: access starting Oct 16, 2017, and you can now see a green secure sign in front of a KDnuggets URL.
One problem with the conversion to https is the loss of Facebook like and share counts for http: version of a page (LinkedIn and Addthis social media counts seem to be unaffected).
Now the Facebook like/share count only shows the likes/shares since Oct 16, 2017, and the total share count on the right side of the page does NOT include the "old" likes.
We don't want our writers to lose their hard-earned likes (about 200,000 likes in total), so we captured the number of http likes in advance of conversion and display them in the social sharing area (below the post title) for posts that have at least 20 likes as http likes NNN. For example,
XGBoost, a Top Machine Learning Method on Kaggle, Explained has 232 "old" likes in addition to new ones.
Here are the top 20 most liked KDnuggets posts prior to Oct 16, 2017:
Enjoy reading KDnuggets with security and please continue to like our posts and pages!
One problem with the conversion to https is the loss of Facebook like and share counts for http: version of a page (LinkedIn and Addthis social media counts seem to be unaffected).
Now the Facebook like/share count only shows the likes/shares since Oct 16, 2017, and the total share count on the right side of the page does NOT include the "old" likes.
We don't want our writers to lose their hard-earned likes (about 200,000 likes in total), so we captured the number of http likes in advance of conversion and display them in the social sharing area (below the post title) for posts that have at least 20 likes as http likes NNN. For example,
XGBoost, a Top Machine Learning Method on Kaggle, Explained has 232 "old" likes in addition to new ones.
Here are the top 20 most liked KDnuggets posts prior to Oct 16, 2017:
- The 10 Algorithms Machine Learning Engineers Need to Know, 9583 likes
- 60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more, 7137
- 10 Free Must-Read Books for Machine Learning and Data Science, 6310
- Python overtakes R, becomes the leader in Data Science, Machine Learning platforms, 4185
- Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?, 3250
- Top 15 Python Libraries for Data Science in 2017, 2268
- Poll: What Predictive Analytics, Data Mining, Data Science software/tools you used in the past 12 months?, 2049
- What is the Difference Between Deep Learning and "Regular" Machine Learning?, 2018
- R vs Python for Data Science: The Winner is ..., 1931
- Top 20 Python Machine Learning Open Source Projects, 1924
- The Most Popular Language For Machine Learning and Data Science Is ..., 1877
- Big Data and the Internet of Things don't make business smarter, Analytics and Data Science do, 1758
- 5 EBooks to Read Before Getting into A Machine Learning Career, 1691
- 7 Steps to Mastering Machine Learning With Python, 1669
- Top Algorithms and Methods Used by Data Scientists, 1662
- 6 Interesting Things You Can Do with Python on Facebook Data, 1651
- New Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?, 1637
- Deep Learning Research Review: Natural Language Processing, 1617
- An Overview of Python Deep Learning Frameworks, 1459
- Machine Learning vs Statistics, 1369
Enjoy reading KDnuggets with security and please continue to like our posts and pages!