—or, at least, something a motivated techie can teach themselves online. Which means more and more enterprises are able to use machine learning to automate, predict, plan, and personalize their products and services.
The impact on business is profound. To avoid this, you need to keep track of whether or not your models are stale. But knowing which of your models are in use and what they are doing is something many companies struggle with. Consider several features all drifting at the same time. This might seem like simple housekeeping compared to the hard math of building neural networks, but maybe that’s why it’s so often overlooked.
What’s more, because so much machine learning development has moved to the cloud, data science veterans like Google now offer opinionated tools that enable your own data science teams to follow those best practices without having to think about them. , a comprehensive managed ML platform that increases the rate of experimentation and accelerates time to business value for AI projects.
“We provide an immersive and personalized experience for people to purchase with confidence whether it’s a virtual try-on at web check out, or helping to understand what brand product is right for each individual,” said Jeff Houghton, chief operating officer at ModiFace, part of L’Oréal.