Source: Forbes | Jan 1, 2019 Author: Janakiram MSV Machine learning platforms are one of the fastest growing services of the public cloud.
Unlike other cloud-based services, ML and AI platforms are available through diverse delivery models such as cognitive computing, automated machine learning, ML model management, ML model serving and GPU-based computing.
This article attempts to explain the terminology and delivery models adopted by public cloud providers.
It aims to help business decision makers choose the right cloud-based ML and AI service.
Like the original cloud delivery models of IaaS, PaaS, and SaaS, ML and AI spectrum span infrastructure, platform and high-level services exposed as APIs.
Let’s take a closer look at each of these layers.
Cognitive Services Cognitive computing is delivered as a set of APIs that offer computer vision, natural language processing (NLP) and speech services.
Developers can consume these APIs like any other web service or REST API.
Developers are not expected to know intricate details of machine learning algorithms or data processing pipelines to take advantage of these services.
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