Alternatives to Amazon Elastic Inference logo

Alternatives to Amazon Elastic Inference

Azure Machine Learning, Amazon SageMaker, Amazon Machine Learning, 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.

Top Alternatives to Amazon Elastic Inference

  • Azure Machine Learning

    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 SageMaker

    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

    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

    Algorithms.io

    Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables ...

  • NanoNets

    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

    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. ...

  • Amazon Personalize

    Amazon Personalize

    Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications. ...

  • Firebase Predictions

    Firebase Predictions

    Firebase Predictions uses the power of Google’s machine learning to create dynamic user groups based on users’ predicted behavior. ...

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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PROS OF AZURE MACHINE LEARNING
    No pros available
    CONS OF AZURE MACHINE LEARNING
      No cons available

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      Amazon SageMaker logo

      Amazon SageMaker

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      Accelerated Machine Learning
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      PROS OF AMAZON SAGEMAKER
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        CONS OF AMAZON SAGEMAKER
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          Julien DeFrance
          Principal Software Engineer at Tophatter · | 2 upvotes · 41.1K views

          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 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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          PROS OF AMAZON MACHINE LEARNING
            No pros available
            CONS OF AMAZON MACHINE LEARNING
              No cons available

              related Amazon Machine Learning posts

              Julien DeFrance
              Principal Software Engineer at Tophatter · | 2 upvotes · 41.1K views

              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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              PROS OF ALGORITHMS.IO
                No pros available
                CONS OF ALGORITHMS.IO
                  No cons available

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                  NanoNets logo

                  NanoNets

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                  Machine learning API with less data
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                  CONS OF NANONETS
                    No cons available

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                    Google AI Platform logo

                    Google AI Platform

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                    Create your AI applications once, then run them easily on both GCP and on-premises
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                    PROS OF GOOGLE AI PLATFORM
                      No pros available
                      CONS OF GOOGLE AI PLATFORM
                        No cons available

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                        Amazon Personalize logo

                        Amazon Personalize

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                        Real-time personalization and recommendation
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                        PROS OF AMAZON PERSONALIZE
                          No pros available
                          CONS OF AMAZON PERSONALIZE
                            No cons available

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                            Firebase Predictions logo

                            Firebase Predictions

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                            Define dynamic user groups based on predicted behavior
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                            PROS OF FIREBASE PREDICTIONS
                              No pros available
                              CONS OF FIREBASE PREDICTIONS
                                No cons available

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