AWS today appear a new apparatus acquirements service, Amazon SageMaker Canvas. Unlike its absolute apparatus acquirements services, the ambition admirers actuality isn’t awful abstruse abstracts scientists and engineers but any architect or business user central a company. The affiance of SageMaker Canvas is that it will acquiesce anybody to body apparatus acquirements anticipation models, appliance a point-and-click interface.
If that sounds familiar, it may be because Azure and others action agnate tools, admitting AWS may accept the advantage that a lot of companies already abundance all of their abstracts in AWS anyway.
Amazon SageMaker Canvas awning shot.
Image Credits: Amazon
“SageMaker Canvas leverages the aforementioned technology as Amazon SageMaker to automatically apple-pie and amalgamate your data, actualize hundreds of models beneath the hood, baddest the best assuming one, and accomplish new alone or accumulation predictions,” writes AWS’s Alex Casalboni in today’s announcement. “It supports assorted botheration types such as bifold classification, multi-class classification, afterwards regression, and time alternation forecasting. These botheration types let you abode business-critical use cases, such as artifice detection, agitate reduction, and account optimization, afterwards autograph a distinct band of code.”
Unsurprisingly, the account is backed by SageMaker, AWS’s absolutely managed apparatus acquirements service.
The accepted abstraction actuality is that users can use any dataset, bottomward to a basal CSV file, and again adjudge which of the columns in this dataset Canvas should predict. There’s no charge to anguish about how to alternation this model. Yet while this is a far easier user acquaintance that appliance acceptable ML tools, we’re still not absolutely talking drag-and-drop either. This is AWS, afterwards all. The all-embracing acquaintance is added affiliated to alive in the AWS animate than a avant-garde no-code application.
apprehend added about AWS re:Invent 2021 on TechCrunch
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