Alternatives to Amazon Elastic Inference logo

Alternatives to Amazon Elastic Inference

Azure Machine Learning, Amazon Machine Learning, Amazon SageMaker, Algorithms.io, and NanoNets are the most popular alternatives and competitors to Amazon Elastic Inference.
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What is Amazon Elastic Inference and what are its top alternatives?

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.
Amazon Elastic Inference is a tool in the Machine Learning as a Service category of a tech stack.

Amazon Elastic Inference alternatives & related posts

Azure Machine Learning logo

Azure Machine Learning

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A fully-managed cloud service for predictive analytics
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    Azure Machine Learning logo
    Azure Machine Learning
    VS
    Amazon Elastic Inference logo
    Amazon Elastic Inference
    Amazon Machine Learning logo

    Amazon Machine Learning

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    Visualization tools and wizards that guide you through the process of creating ML models w/o having to learn...
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      Amazon Machine Learning logo
      Amazon Machine Learning
      VS
      Amazon Elastic Inference logo
      Amazon Elastic Inference

      related Amazon Machine Learning posts

      Julien DeFrance
      Julien DeFrance
      Principal Software Engineer at Tophatter | 2 upvotes 24.7K views
      atSmartZipSmartZip
      Serverless
      Serverless
      AWS Lambda
      AWS Lambda
      Amazon Machine Learning
      Amazon Machine Learning
      Amazon SageMaker
      Amazon SageMaker
      #PaaS
      #GCP
      #FaaS

      Which #IaaS / #PaaS to chose? Not all #Cloud providers are created equal. As you start to use one or the other, you'll build around very specific services that don't have their equivalent elsewhere.

      Back in 2014/2015, this decision I made for SmartZip was a no-brainer and #AWS won. AWS has been a leader, and over the years demonstrated their capacity to innovate, and reducing toil. Like no other.

      Year after year, this kept on being confirmed, as they rolled out new (managed) services, got into Serverless with AWS Lambda / FaaS And allowed domains such as #AI / #MachineLearning to be put into the hands of every developers thanks to Amazon Machine Learning or Amazon SageMaker for instance.

      Should you compare with #GCP for instance, it's not quite there yet. Building around these managed services, #AWS allowed me to get my developers on a whole new level. Where they know what's under the hood. Where they know they have these services available and can build around them. Where they care and are responsible for operations and security and deployment of what they've worked on.

      See more
      Amazon SageMaker logo

      Amazon SageMaker

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      Accelerated Machine Learning
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        Amazon SageMaker logo
        Amazon SageMaker
        VS
        Amazon Elastic Inference logo
        Amazon Elastic Inference

        related Amazon SageMaker posts

        Julien DeFrance
        Julien DeFrance
        Principal Software Engineer at Tophatter | 2 upvotes 24.7K views
        atSmartZipSmartZip
        Serverless
        Serverless
        AWS Lambda
        AWS Lambda
        Amazon Machine Learning
        Amazon Machine Learning
        Amazon SageMaker
        Amazon SageMaker
        #PaaS
        #GCP
        #FaaS

        Which #IaaS / #PaaS to chose? Not all #Cloud providers are created equal. As you start to use one or the other, you'll build around very specific services that don't have their equivalent elsewhere.

        Back in 2014/2015, this decision I made for SmartZip was a no-brainer and #AWS won. AWS has been a leader, and over the years demonstrated their capacity to innovate, and reducing toil. Like no other.

        Year after year, this kept on being confirmed, as they rolled out new (managed) services, got into Serverless with AWS Lambda / FaaS And allowed domains such as #AI / #MachineLearning to be put into the hands of every developers thanks to Amazon Machine Learning or Amazon SageMaker for instance.

        Should you compare with #GCP for instance, it's not quite there yet. Building around these managed services, #AWS allowed me to get my developers on a whole new level. Where they know what's under the hood. Where they know they have these services available and can build around them. Where they care and are responsible for operations and security and deployment of what they've worked on.

        See more
        Algorithms.io logo

        Algorithms.io

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        Machine learning as a service for streaming data from connected devices.
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          Algorithms.io logo
          Algorithms.io
          VS
          Amazon Elastic Inference logo
          Amazon Elastic Inference
          NanoNets logo

          NanoNets

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          Machine learning API with less data
          NanoNets logo
          NanoNets
          VS
          Amazon Elastic Inference logo
          Amazon Elastic Inference
          FloydHub logo

          FloydHub

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          Heroku for Deep Learning
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            FloydHub logo
            FloydHub
            VS
            Amazon Elastic Inference logo
            Amazon Elastic Inference
            Amazon Personalize logo

            Amazon Personalize

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            Real-time personalization and recommendation
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              Amazon Personalize logo
              Amazon Personalize
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              Amazon Elastic Inference logo
              Amazon Elastic Inference
              BigML logo

              BigML

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              Machine Learning, made simple. Predictive analytics for big data and not-so-big data.
              BigML logo
              BigML
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              Amazon Elastic Inference logo
              Amazon Elastic Inference