Tim Oates

Ask Tim: Using Machine Learning to Detect Objects with No Data

What’s the most important and difficult part of a successful machine learning project? Take a second to ponder that question. There are probably lots of valid answers, but in my experience it’s the data. Is there enough of it? Where is it stored? Is it clean or noisy? Does it have all of the information we need? I’ve found that the amount of high quality data and the cleverness required of your machine learning team are inversely related.  

It’s not surprising that a lot of effort has been put into approaches to ML that need less and less data. We’ll focus on supervised learning, where the data consists of things and labels: emails and whether they’re spam, infrared images of concrete and whether defects are present, credit card transactions and whether they’re fraudulent.