Amazon Elastic Inference vs GraphLab Create

Amazon Elastic Inference

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GraphLab Create

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Amazon Elastic Inference vs GraphLab Create: What are the differences?

Amazon Elastic Inference: 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; GraphLab Create: Machine learning platform that enables data scientists and app developers to easily create intelligent apps at scale. Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

Amazon Elastic Inference and GraphLab Create can be categorized as "Machine Learning as a Service" tools.

Pros of Amazon Elastic Inference
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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 GraphLab Create?

    Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.
    What companies use Amazon Elastic Inference?
    What companies use GraphLab Create?
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      What tools integrate with Amazon Elastic Inference?
      What tools integrate with GraphLab Create?
        No integrations found
        What are some alternatives to Amazon Elastic Inference and GraphLab Create?
        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.
        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.
        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.
        See all alternatives
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