- Version 0.9.36
- Sold by Outpace Systems
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
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
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
Predicts the yearly income in USD based on personal information. Provide the input data in JSON format. The model was trained using an open dataset of non-identifiable data attributes. The model is deployed using a KNIME workflow (www.knime.com).
Model Package - Fulfilled on Amazon SageMaker
The CV19 Index (https://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
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
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