Search Results for "learning vector quantization"
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Showing 2 open source projects for "learning vector quantization"
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Context for your AI agentsBuild data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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Aerosolve
A machine learning package built for humans
Aerosolve is an open-source machine learning library developed by Airbnb, designed for interpretable and human-friendly modeling. Built around sparse, human-intuitive features (like geography, pricing), it supports feature quantization, interaction specification, and rule-based priors—enabling domain experts to contribute directly to model behavior. -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. ...
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