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Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

RocketML Image Embeddings using SVD
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By: RocketML Latest Version: 0.1

Product Overview

Image Embeddings using Singular Value Decomposition (SVD) can be used for semantic search, dimensionality reduction, and anomaly detection. Given a batch of images, singular values and vectors are computed using this algorithm.

Key Data

By RocketML
Type Algorithm
Fulfillment Methods Amazon SageMaker

Usage Information

Support Information

RocketML Image Embeddings using SVD

RocketML offers free support with email response as well as one-on-one office hours with our experienced solution architects. The service helps customers of all sizes and technical abilities to make best use of RocketML products and features. Subscribers and prospecting customers can contact us at the URL below or email

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