Amazon Elastic Inference vs. IBM SPSS Modeler
| Product | Rating | Most Used By | Product Summary | Starting Price |
|---|---|---|---|---|
 Amazon Elastic Inference | N/A | N/A | Amazon Elastic Inference allows users to attach just the right amount of GPU-powered inference acceleration to any Amazon EC2 instance, Amazon SageMaker instance, or ECS task. Users pay for the accelerator hours used. It is designed to be used with AWS’s enhanced versions of TensorFlow Serving, Apache MXNet and PyTorch, which automatically detect the presence of inference accelerators, and optimally distribute the model operations between the accelerator’s GPU and the instance’s CPU. | N/A |
 IBM SPSS Modeler | Score7.1 out of 10 | N/A | IBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets. | $499 per month |
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| Editions & Modules | No answers on this topic |
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| Entry-level Setup Fee | No setup fee | Optional | ||||||||||||||
| Additional Details | — | IBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact. | ||||||||||||||
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| Likelihood to Recommend | - | 7.0 |
| Usability | - | 8.0 |
| Support Rating | - | 10.0 |