Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
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Updated
Jun 12, 2024 - Rust
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Collection of notes on things I find interesting
Versatile End-to-End Recommender System
Fullstack movie data application where users can find information about different movies with reviews and ratings and get recommendations. Movie data is fetched from TMDB API
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Radient turns many data types (not just text) into vectors for similarity search, clustering, regression analysis, and more.
Pytorch domain library for recommendation systems
Batch Inference code for generating video content recommendations from Reinforcement Learning based recommender system. Built with SpringBoot
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
HierarchicalKV is a part of NVIDIA Merlin and provides hierarchical key-value storage to meet RecSys requirements. The key capability of HierarchicalKV is to store key-value feature-embeddings on high-bandwidth memory (HBM) of GPUs and in host memory. It also can be used as a generic key-value storage.
Merlin Systems provides tools for combining recommendation models with other elements of production recommender systems (like feature stores, nearest neighbor search, and exploration strategies) into end-to-end recommendation pipelines that can be served with Triton Inference Server.
NCF Recommender System (Pytorch)
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.
XBRecs is an explainable book recommender system which bases its recommendations on book descriptions manipulated using NLP techniques.
Session-weighted recommendation system in Python
推荐系统入门教程,在线阅读地址:https://datawhalechina.github.io/fun-rec/
BARS: Towards Open Benchmarking for Recommender Systems https://openbenchmark.github.io/BARS
[SIGIR'2024] "SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation"
A Repository chatbot and Recommendation system for Github users.
Perform analysis and Basic Recommendations based on Similar Genres and Movies which Users prefer.
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