Amazon Elastic Inference vs Amazon Machine Learning vs Amazon SageMaker

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Amazon Elastic Inference

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Amazon Machine Learning

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Amazon SageMaker

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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 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.

What is 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.

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What companies use Amazon Elastic Inference?
What companies use Amazon Machine Learning?
What companies use Amazon SageMaker?

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What tools integrate with Amazon Elastic Inference?
What tools integrate with Amazon Machine Learning?
What tools integrate with Amazon SageMaker?
    No integrations found

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    What are some alternatives to Amazon Elastic Inference, Amazon Machine Learning, and Amazon SageMaker?
    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.
    Algorithms.io
    Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables
    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.
    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.
    Amazon Personalize
    Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.
    See all alternatives