Amazon Elastic Inference vs GraphLab Create

Overview

GraphLab Create

Stacks8

Followers40

Votes3

Amazon Elastic Inference

Stacks45

Followers56

Votes0

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.

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Detailed Comparison

GraphLab Create	Amazon Elastic Inference
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 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.
Analyze terabyte scale data at interactive speeds, on your desktop.;A Single platform for tabular data, graphs, text, and images.;State of the art machine learning algorithms including deep learning, boosted trees, and factorization machines.;Run the same code on your laptop or in a distributed system, using a Hadoop Yarn or EC2 cluster.;Focus on tasks or machine learning with the flexible API.;Easily deploy data products in the cloud using Predictive Services.;Visualize data for exploration and production monitoring.	-
Statistics
Stacks 8	Stacks 45
Followers 40	Followers 56
Votes 3	Votes 0
Pros & Cons
Pros 1 Intelligent Function Defaults 1 Fast Data Summary 1 Simple Machine Learning Tools	No community feedback yet
Integrations
No integrations available	TensorFlow Amazon EC2 Amazon SageMaker

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