Develop a system that personalizes music recommendations for users and analyzes their engagement and retention.
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Updated
Jun 13, 2024 - Jupyter Notebook
Develop a system that personalizes music recommendations for users and analyzes their engagement and retention.
If you don't know what to watch among the animes or mangas you have in your plan-to-watch list, use this. You can sort them by score, members and favorites.
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.
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Repository of recommender systems data and model information
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Recommendation System for Books using Collaborative Filterings: An ML Project to Recommend 'n' similar Books for a given book, as per the Collaborative users' ratings of the books. This Project also involves the deployment in a Flask Based web application.
R-Package that contains misc functions for data science and to streamline the development of decision support and business analytics systems
Pytorch domain library for recommendation systems
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
Versatile End-to-End Recommender System
AI 추천 서비스 기반 도서 e-커머스
Collection of notes on things I find interesting
A framework for large scale recommendation algorithms.
Radient turns many data types (not just text) into vectors for similarity search, clustering, regression analysis, and more.
Batch Inference code for generating video content recommendations from Reinforcement Learning based recommender system. Built with SpringBoot
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.
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