Amazon Elastic Inference vs Inferrd

Overview

Amazon Elastic Inference

Stacks45

Followers56

Votes0

Inferrd

Stacks2

Followers11

Votes10

Amazon Elastic Inference vs Inferrd: What are the differences?

Developers describe Amazon Elastic Inference as "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. On the other hand, Inferrd is detailed as "*Deploy ML Models with a Simple Drag and Drop *". It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

Amazon Elastic Inference and Inferrd belong to "Machine Learning as a Service" category of the tech stack.

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Detailed Comparison

Amazon Elastic Inference	Inferrd
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.	It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.
-	Machine Learning practioners don't need to wait for engineering to deploy their models anymore; No need to invest in expensive infrastructure and tooling. Inferrd starts at $14, batteries included; Built with security in mind. Your models are protected using state-of-the-art encryption at rest.
Statistics
Stacks 45	Stacks 2
Followers 56	Followers 11
Votes 0	Votes 10
Pros & Cons
No community feedback yet	Pros 3 Easy to use 2 Very quick response time 2 Fast 2 Secure 1 Fair pricing
Integrations
TensorFlow Amazon EC2 Amazon SageMaker	TensorFlow SpaCy Keras scikit-learn

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