Amazon Elastic Inference vs Azure Machine Learning

Amazon Elastic Inference

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Azure Machine Learning

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Amazon Elastic Inference vs Azure Machine Learning: What are the differences?

Developers describe Amazon Elastic Inference as "GPU-Powered Deep Learning Inference Acceleration". Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon. On the other hand, Azure Machine Learning is detailed as "A fully-managed cloud service for predictive analytics". Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

Amazon Elastic Inference and Azure Machine Learning belong to "Machine Learning as a Service" category of the tech stack.

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What is Amazon Elastic Inference?

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon.

What is Azure Machine Learning?

Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.
What companies use Amazon Elastic Inference?
What companies use Azure Machine Learning?

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What tools integrate with Amazon Elastic Inference?
What tools integrate with Azure Machine Learning?
What are some alternatives to Amazon Elastic Inference and Azure Machine Learning?
Amazon SageMaker
A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.
Amazon Machine Learning
This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.
Algorithms.io
Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables
NanoNets
Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.
Google AI Platform
Makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively.
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How much does Amazon Elastic Inference cost?
How much does Azure Machine Learning cost?
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