Quid maintains an incredibly diverse set of company descriptions. A priority for Quid is identifying company descriptions of poor quality and improving them before they even get into our index. Ben Bowles, a resident data scientist, wrote up a great article featured on our parent blog on our approach to separating the “good” from the “bad” with very little data to go on: We developed a strategic goal at Quid to use machine learning to identify marketing language that conveys very little information. In fact, we combined this goal with recent advances in deep learning and a bit of an experiment: to see whether deep learning really requires “big data,” or whether small data can suffice. Read more on our approach to deep learning with small data on quid.com. Interested in helping us solve awesome problems? If so, then head over to our careers page!Read More
- How does Quid create reliable business intelligence?
- Our First Engineering Game Day
- Improving search with Word2Vec and Wikipedia
- Managing text data you haven’t seen and can’t control
- Using deep learning with small data
- It’s NOT the Stork: Where Tests Come From
- Quid Hackathon II
- Here’s a suggestion
- Optimizing The Rendering Engine
- Quid Hackathon
- Major League Data Visualization Event @ Quid!
- The Ups and Downs of a Chef Shop
- Reaching Equilibrium in Web Browser Network Visualizations