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There are three routes you can go with this. The simplest would probably be to use Microsoft's Face API, which is part of their Azure Cognitive Services platform. All of the computing is done in the cloud, and at least for your purposes, the modelling necessary to detect faces has already been performed by Microsoft, so it's a single method call to send it a picture and receive back a bounding box. The caveat is... Source: over 1 year ago
Azure Cognitive Services provide a few interesting AI as a service offerings beyond CLU & LUIS that can be helpful for conversational AI:. - Source: dev.to / over 1 year ago
Hello, not sure about the quality of this API as I’ve just heard about it but thought it might help you: Azure Cognitive Services. Source: over 1 year ago
Cognitive Services Https://azure.microsoft.com/en-us/services/cognitive-services/. - Source: dev.to / almost 2 years ago
Microsoft Azure offers an umbrella service known as Cognitive Services. This service provides AI capabilities that you can integrate into your existing applications through a single managed area. - Source: dev.to / about 2 years ago
There’s also the ML as a service (MLaaS) movement that lowers the barrier for common ML capabilities (eg image object detection and audio transcription). Basically, you use APIs. See: https://aws.amazon.com/machine-learning/. Source: over 1 year ago
Do you have questions about Data Science and ML on AWS - https://aws.amazon.com/machine-learning/. Source: about 3 years ago
Open Text Magellan - OpenText Magellan - the power of AI in a pre-wired platform that augments decision making and accelerates your business. Learn more.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Veritone Automate Studio - Veritone Automate Studio is one of the major Low-Code platforms powered by AI to empower organizations willing to implement intelligent process automation initiatives to create and deploy workflows backed by AI and integrate the output insights into…
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Apple Machine Learning Journal - A blog written by Apple engineers