Data science blogs I follow, and you should too

Working within the Data Science industry has made me religiously follow a few blogs that I use to stay up to date with industry trends, learn new concepts, and learn the language of the industry. As a marketer, these three things are essential to know. These are the data science blogs I follow, and you should too.

R-bloggers began when creator, Tal Galili, was fed-up with trying to find blogs about R. Instead of continuing his search, Tal created a site that pulls feeds from contributing blogs. R-bloggers "is a blog aggregator of content contributed by bloggers who write about R". If your blog is all about R, you can create an RSS feed and contribute to the "R blogosphere". This aggregator is a great place to find different blogs, especially if you're new to the industry (like me).

Whether you enjoy data science is a hobby or a profession, you should be reading Towards Data Science (TDS). In October 2016 TDS joined Medium with the goal of "gathering good posts and distribute the to a broader audience". Now, Towards Data Science includes 1,500 authors from around the world. TDS offers contributors an editorial team to help raise the quality of posts being submitted. While reading an article on TDS, you know you're getting high quality content you can trust.

KDnuggets is another staple of data science blogs. The site has received so many impressive awards, I'm not going to list any. You can view them yourself.

It may seem messy when you first visit, but, much like original Reddit users, That's the way I like it, and the 500,000 monthly visitors would probably agree. Posts range from courses and tutorials to news, meetings, and opinions. Like TDS, KDnuggets offers high quality content you can trust to help you learn.

Entrepreneur is different than the three blogs above. Instead of focusing solely on anything within data science, it keeps its content specifically about how data science and big data effect entrepreneurship and small business. This blog is great for entrepreneurs and small business owners who want to absorb the concepts into their own business. The market for using data science to make data-driven business decisions is growing and should not be overlooked.

One of my favorite things about DataFloq is how easy it is to navigate the site. It has a list of tags at the top of the articles page that makes sorting through the posts very easy. It's also easy to find events going on around the world.

The blog itself is always focuses mainly on big data, artificial intelligence, and new technologies. There is always a new article to read about one of the topics you are interested in. You can also view how many views the article has received without having to click on it. I use that to give me an idea of what the quality of the content is like within the post. The higher the views, typically the higher the quality of content will be. If you're looking for anything to do with new, emerging technologies, I suggest browsing DataFloq.

I use Dataconomy almost strictly for learning about the trends with blockchain. It isn't updated as DataFloq, or the other above blogs, but it still gives helpful insights into what is trending within the data science industry.

Dataconomy prides itself in having a global network of contributors that don't just look at the major tech companies. Authors are encouraged to find new and promising tech startups that will take the world by storm.

Who do you follow?

Is there a data science blog you think I missed? Let me know! Follow the link below to start a discussion. I'm always looking for new blogs to read to continue my data science education and learn new industry trends.

This is a companion discussion topic for the original entry at

If you are interested in general AI, Machine Learning and Data Science then you should definitely follow Data Science Central. If you are interested in Natural Language Processing and the advancements related to this field then do follow Sebastian Ruder. For the purpose of tutorials head over to the ultimate HackerNoon.