Glean is the AI-powered work assistant that searches across all of your company's data to help you find the answers you need. It's the enterprise-grade solution for bringing generative AI into the workplace: the single place where you can get answers that are grounded in your company's...
Linux/Unix, Ubuntu 20.04.1 LTS - 64-bit Amazon Machine Image (AMI)
A recommender model that learns a matrix factorization embedding based off minimizing the pairwise ranking loss described in the paper.
Algorithm - Fulfilled on Amazon SageMaker
The CV19 Index (http://cv19index.com) is an open source, AI-based predictive model that identifies people likely to have heightened vulnerability to complications from COVID-19. The index is intended to help hospitals and government agencies respond to COVID-19. By targeting their outreach...
Model Package - Fulfilled on Amazon SageMaker
Key phrase extractor uses end-to-end text extraction pipeline, text analysis and natural language processing techniques to automate key phrases/words extraction from text documents. This solution is based on unsupervised graph-based, topic-based, statistics-based algorithms for the construction of...
Model Package - Fulfilled on Amazon SageMaker
Public LTR trainings are delivered via the online platform Moodle. This combines prerecorded video from members of the OSC team, slides, labs and quizzes so you make sure you’ve covered all the material. Learn how to: Interact with the Solr, OpenSearch & Elasticsearch Learning to Rank plugins Use...
A recommendation model using an alternating least squares factorization approach for implicit datasets.
Algorithm - Fulfilled on Amazon SageMaker
An explicit feedback matrix factorization model. Uses a classic matrix factorization approach, with latent vectors used to represent both users and items. Their dot product gives the predicted score for a user-item pair.
Algorithm - Fulfilled on Amazon SageMaker
A recommender model that learns a matrix factorization embedding based off minimizing the pairwise ranking loss described in the paper.
Algorithm - Fulfilled on Amazon SageMaker
Models for recommending items given a sequence of previous implicit user/item interactions. Solves user cold start problem.
Algorithm - Fulfilled on Amazon SageMaker
An implicit feedback matrix factorization model. Uses a classic matrix factorization approach, with latent vectors used to represent both users and items. Their dot product gives the predicted score for a user-item pair. The model is trained through negative sampling: for any known user-item pair,...
Algorithm - Fulfilled on Amazon SageMaker
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