AWS immediately introduced a new machine studying service, Amazon SageMaker Canvas. Unlike its present machine studying companies, the audience right here isn’t extremely technical information scientists and engineers however any engineer or enterprise consumer inside a firm. The promise of SageMaker Canvas is that it’s going to permit anyone to construct machine studying prediction fashions, utilizing a point-and-click interface.
If that sounds acquainted, it might be as a result of Azure and others provide related instruments, although AWS might have the benefit that a lot of firms already retailer all of their information in AWS anyway.
“SageMaker Canvas leverages the identical know-how as Amazon SageMaker to robotically clear and mix your information, create lots of of fashions beneath the hood, choose the most effective performing one, and generate new particular person or batch predictions,” writes AWS’s Alex Casalboni in immediately’s announcement. “It helps a number of downside sorts akin to binary classification, multi-class classification, numerical regression, and time sequence forecasting. These downside sorts allow you to deal with business-critical use circumstances, akin to fraud detection, churn discount, and stock optimization, with out writing a single line of code.”
Unsurprisingly, the service is backed by SageMaker, AWS’s totally managed machine studying service.
The common thought right here is that customers can use any dataset, all the way down to a primary CSV file, after which resolve which of the columns on this dataset Canvas ought to predict. There’s no want to fret about practice this mannequin. Yet whereas that is a far simpler consumer expertise that utilizing conventional ML instruments, we’re nonetheless not fairly speaking drag-and-drop both. This is AWS, in any case. The general expertise is extra akin to working within the AWS console than a trendy no-code software.
AWS gets a no-code ML service – TechCrunch
