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Data Science

Machine learning & data science for beginners and experts alike.
SusanCS
Alteryx Community Team
Alteryx Community Team

My social media feeds largely consist of news headlines, puppies, baked goods, and friends’ vacation photos. However, I’ve got a little data science sprinkled in, just the right amount to jolt my brain awake occasionally as I mindlessly scroll.

 

If you want to keep your social media time focused on fun, I respect that — but if you want those social algorithms to show you actual algorithms, keep reading. I’ll share some accounts and communities to follow for easy, at-a-glance access to good ideas and tips you can implement.



Twitter

On Twitter, I follow a lot of data science news sources, but I also appreciate accounts that often share straightforward morsels of information in just 280 characters, without linking to longer resources.

 

  • Data Science Fact (@DataSciFact) posts quick facts about a wide variety of data science concepts. 

 

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  • Daily Python Tip (@python_tip) offers a neatly summarized idea or tool suggestion each day. 

 

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  •  One R Tip a Day (@RLang Tip) is run by the R community team at Microsoft and provides, as you’d guess, a daily R tip.

     

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  • Probability Fact (@ProbFact) offers a probability concept or insight every day.

 

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LinkedIn

In addition to learning from what people in your network share, there are other ways to glean useful data science info from LinkedIn.

 

    • Follow hashtags. You can get a wider variety of information on topics of interest by following specific hashtags on LinkedIn (similar to how you can follow a hashtag on Instagram). For example, #datascience is used on many articles, videos, and other posts. LinkedIn will insert some of these hashtagged items into your main feed.

 

 



Reddit

Each data-related subreddit has its own focus and ambiance. Here are a few to check out, but there are many more to explore.

    • r/datascience: This is a lively community with over half a million members. There’s a weekly thread for discussions about learning data science and entering the field. It’s fairly strict about content and actively moderated.
    • r/MachineLearning: This subreddit is huge (1.9 million members) and can be more technical, with many posts focused on sharing and discussing cutting-edge academic publications.

 

 

  • r/learnmachinelearning: This group is more accessible for those just starting out with machine learning, though discussions can still dive pretty deep. It’s a bit more welcoming toward beginner-level questions than the two subreddits above.
  • r/statistics: This community is a space for “all things dealing with statistical theory, software, and application.” You can safely explore even the most obscure corners of statistics here.



Instagram

Yes, among the influencers and #sponsored posts, there’s some educational data science content! 

  • @bigdataqueen offers a fresh take on data science and ML that will pop in your feed, with well-designed graphics and thorough, informative captions.

 

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  • @pycoders posts cheat sheets and quick tips, plus a healthy quantity of memes so you can take a break from the serious stuff (and find fun things to share with coworkers).

 

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  • @data_science_learn shares some informative posts on stats topics and various tools for data science — and, again, ample memes.

 

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  • Women Who Code has specialized Instagram accounts related to data science and Python, among other topics. The Python account observes “Trivia Tuesday” each week to help you review Python fundamentals, and the data science account offers video snippets and stats review posts.

 

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What are your favorite ways to inject a little data science into your social media feeds? Who else should we all follow? Share your favorites in the comments below, and be sure to subscribe to the blog to get future articles delivered to your inbox.



Blog teaser photo by Rodion Kutsaev on Unsplash

Susan Currie Sivek
Senior Data Science Journalist

Susan Currie Sivek, Ph.D., is the data science journalist for the Alteryx Community. She explores data science concepts with a global audience through blog posts and the Data Science Mixer podcast. Her background in academia and social science informs her approach to investigating data and communicating complex ideas — with a dash of creativity from her training in journalism. Susan also loves getting outdoors with her dog and relaxing with some good science fiction. Twitter: @susansivek

Susan Currie Sivek, Ph.D., is the data science journalist for the Alteryx Community. She explores data science concepts with a global audience through blog posts and the Data Science Mixer podcast. Her background in academia and social science informs her approach to investigating data and communicating complex ideas — with a dash of creativity from her training in journalism. Susan also loves getting outdoors with her dog and relaxing with some good science fiction. Twitter: @susansivek

Comments
Emil_Kos
16 - Nebula

Hi @SusanCS,

 

I really like this article. I wonder how many people are aware of how significant an impact their Facebook(and other social media) wall has on the content they consume.

Following the right people can significantly influence your life, and sharing an article like that might be very helpful for people starting in the area of data science.

Thank you for sharing.

SusanCS
Alteryx Community Team
Alteryx Community Team

Glad you enjoyed it, @Emil_Kos! I've liked mixing these accounts into my own feeds and appreciate the little doses of learning I get from them. Some of my social media interactions have led to personal connections, too, which is awesome. Let us know if you find more accounts worth following!