The "Aha" Moment: How to Onboard an API Service and Get Active Users
Introducing Serverless Data Feeds
Share Data Without Sharing Credentials: Introducing Pipe-level Permissions
How to Embed a Live, Refreshable D3.js Chart into GitHub Pages
A 90 Degree Tilt: Introducing Vertical Pipes
A Simple Pipe Routing Example: HTML Upload to HTML Display
Introducing our API and Command Line Interface: Flex.io for Developers
Just Binge-Listened to 95 SaaStr Podcasts, Here's What I Learned
Thoughts on the Data Ecosystem
The Flex.io Blog
Much electronic ink has been spilled on the rise of the data scientist.
They’ve been called sexy. They’ve been called unicorns. And, we clearly see a direct correlation between this recent adulation and the uptick in searches for “sexy unicorn”. (At least, I hope that’s the reason).
In an excellent post, CIO Isaac Sacolick asks, what technologies work best for decentralized data scientists?
I recently found an article discussing the four different types of Data Scientists. Turns out there’s a quite a bit of wiggle in what the term “Data Scientist” might mean – from business savant to data viz wiz to world class coder to Ph.D. in statistics. A question is posed:
Recently, we’ve been seeing a lot of news about the promise of emerging applications for machine vision.
Much of it’s at the trial stage at this point, particularly with Google Glass and related projects. For instance, the police in Dubai are testing facial recognition on the streets, ER doctors are exploring uses for quick access to critical medical records and Walgreens is experimenting with augmented reality in stores.