Amazon Personalize vs Metarank
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications. | It makes it easy to personalize any listing: recommendations, articles, and search results. Developers make one reranking API call, and Metarank takes care of ML feature updates, model training, and improving target goals like CTR/conversion. |
Combine customer and contextual data to generate high-quality recommendations; Automated machine learning; Continuous learning to improve performance; Bring your own algorithms; Easily integrate with your existing tools; | Built-in feature store to compute features used for online and offline training;
REST API, Kafka, Apache Pulsar connectors to receive events and metadata updates;
Offline and online (real-time personalization) operation modes;
Explain mode to understand how final ranking is computed;
Local mode to run Metarank locally without deploying to a cluster;
Cloud native: deploy Metarank to Kubernetes or AWS |
Statistics | |
GitHub Stars - | GitHub Stars 2.2K |
GitHub Forks - | GitHub Forks 102 |
Stacks 20 | Stacks 2 |
Followers 62 | Followers 9 |
Votes 0 | Votes 0 |
Integrations | |
| No integrations available | |
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