The past month we’ve been busy crafting more content about Beneath. Here are some of the highlights 👇
We’ve completely revamped the Beneath repo on Github. If you like what you see, we’d really appreciate a star ⭐️ to help other people discover the project!
Here’s what’s changed on Github:
Here’s the repo: github.com/beneath-hq/beneath.
Eric has just published a new blog post on dev.to about how you can use Beneath to turn a Pandas data frame into a full-fledged API with a single line of Python code. It’s pretty neat and also includes a useful script to analyze Git commits data. Check it out here.
We often talk about making it easier to put data science into production. But what does “production” really mean and why can it be so hard for analytics and data science projects?
To better showcase that, we wrote a blog post that illustrates what the conventional path looks like for turning a machine learning model into a production data app by laying out the design and evolution of a simple Reddit analytics tool. Read it here.
We’ve published a handful of new quick starts, including two for putting machine learning into production with Beneath:
We’ve also updated several other quick starts with small helper videos.
We’ve made a lot of small UX changes and improvements to the Beneath web console and client libraries. One itch we’ve finally scratched is letting you manage organization and project membership directly in the web console! We’ve also updated our landing page with better graphics and simpler messaging.
Thanks for tuning in! As always, if you are considering using Beneath for your next project or have any other questions, you’re very welcome to contact us.
Until next time 👋