10 Resources Every Data Expert Should Follow
In 2017, artificial intelligence and machine learning went mainstream. These technologies have crossed the chasm from buzzword status to having a measurable impact on our daily lives—just think of how close we are to self-driving cars on the road.
Machine learning algorithms are also becoming a staple in how businesses are run, and the frenetic pace of development means that it is getting increasingly harder to separate signal from noise. As a professional working in this space, I find it is getting harder to stay abreast of developments as they happen.
As such, I’ve put together a list of resources I’m currently using to stay up to date on the latest news in the data science and analytics space.
I should qualify this list by stating what I do for a living: I’m a growth consultant at Outshine. We use data science and analytics to research and implement revenue growth opportunities for our B2B clients. I’m specifically interested in the business applications of machine learning algorithms.
Here are my top 10 recommended resources for all things data analytics, data science, and machine learning:
1. Python Weekly
I use Python as my go-to language for scripting, API development, and analytics. If you’re not familiar with Python, this general purpose programming language is fast becoming one of the most important skills for data analytics (with R being the other contender).
In my opinion, Python Weekly is the best source of articles, training, and code examples related to Python. Even though the newsletter is geared toward a more general Python audience, most of the articles of late deal with data science issues. You can sign up for the newsletter here. Python weekly is curated by @rahulgchaudhary, and is published every Thursday.
DataElixir is an invaluable newsletter on machine learning, modeling techniques, and data analytics, curated by @lonriesberg. My tip: you don’t have to sign up for the newsletter—you can bookmark the site instead (or sign up for the Safari notifications).
Think Hacker News, but for data. Run by Rohit Sivaprasad, the site doesn’t have the scale of Hacker News yet, but I usually check DataTau once a week to find out what the most upvoted links are. There’s usually some overlap with the links curated at DataElixir.
4. The Analytics Dispatch (Mode Analytics)
Every week, the awesome people over at Mode Analytics put together a list of the top 4 articles they've been reading in the data science world. What I find unique about The Analytics Dispatch is the focus on building a strong data culture within your organization. I recommend this newsletter if you’re getting started with building a data team.
Sign up for The Analytics Dispatch here, delivered on Monday at 12pm EST.
5. Data Science Weekly Newsletter
Data Science Weekly is the most “data science-y” of the newsletters that I follow—and by that I mean that the articles curated have more theory about machine learning and AI that the other resources I’ve already mentioned. If you’re looking for business intelligence knowledge, this may not be the best resource.
6. Inside AI
Inside AI is a newsletter focused on news and analysis of trends in artificial intelligence. Curated by Rob May, I love how he separates the newsletter into the “Big Idea,” where he previews a talk or an article, a set of “Must Read Links,” and Commentary on the week’s developments in the AI space. The commentary is highly recommended. Sign up here.
7. O’Reilly Data Newsletter
If you’re looking for information on the technical side of data science, then the O’Reilly Data Newsletter is a must-have.
Caution: the articles curated in this newsletter tend to be geared towards more advanced practitioners of data science. They’re highly insightful, but may not be the best reading material for those just starting out in the field. Check it out here.
8. Kaggle Blog
Kaggle is a platform for data science competitions where statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies. Said another way, that means companies can use Kaggle to find data scientists and machine learning experts to help solve their business problems, usually for a cash prize.
If you’re interested in understanding how companies are using data science to solve business problems, sign up for the Kaggle blog, No Free Hunch, here.
9. Reddit r/datascience
I have to be honest and say that I’m not a huge fan of Reddit (it’s the UI, not the content!). But that said, I do skim the r/datascience subreddit once a week to see what people in the community are talking about. If you’re a Redditor, then this is for you.
10. The Data Skeptic Podcast
I don’t know about you, but my weekly podcast budget is maxed out. Between 99% Invisible, TED Radio Hour and Freakonomics Radio, I barely have time to squeeze in more podcasts. Even so, I still find time every week for Data Skeptic, and you should too.
These are the top 10 resources I use to stay up to date on what’s happening in the ever-changing world of data. What blogs, podcasts, or other resources do you swear by?