One of the big reasons we created our Data for Everyone initiative is that there simply aren't a ton of great open datasets out there for small businesses, startups, and academics to do work on. Sure, there are plenty of small, toy-sized datasets but those simply aren't big enough to create algorithms that anyone can trust. In fact, our founder Lukas wrote as much in his post on Computer World:
Last Thursday, we sat down with a couple great data scientists from Oracle to learn how they use people-powered sentiment analysis. Our CEO Lukas Biewald was joined by Randall Sparks (Principal Member of Technical Staff at Oracle Data Cloud) and Pallika Kanani (Senior Research Staff Member at Oracle Labs) for the session and the folks at Oracle showed us how they create training sets, iterate on their algorithms, and explained how they handle sentiment across multiple languages. We had a lot of questions in the Q&A we couldn't get to, so we'll be answering those below. To start, here's a recording of our chat if you weren't able to join us:
If you read much news after the Republican debate in Cleveland last Thursday, chances are you were slightly frightened that reputable outlets like CNN were all agog over Donald Trump, a man with complicated hair who has a habit of saying bad and gross things pretty much every time he opens his gob. But it wasn't his performance, per se, that had news outlets excited; it was his presence.
Three data scientists, one fantastic webinar.
The thing I noticed when I first visited CrowdFlower was the television. I'd come in early for my first interview and found myself staring at it, but not because the monitor was displaying metrics like you might expect. It was a slide-show with people and their quotes, the contributors who work on CrowdFlower's platform. And it wasn’t all the different people, but one specific image that struck me: a picture of a man named Gerandy from Laguna, Philippines with a quote saying how CrowdFlower has allowed him to earn enough income to help his family.