OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Updated
Jun 12, 2024 - C++
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Pytorch domain library for recommendation systems
Local recommendation system
This project aims to analyze the interactions that users have with articles on the IBM Watson Studio platform, and make recommendations to them about new articles
This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.
An AI-powered application that makes personalized place suggestions. Supported by TÜBİTAK.
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.
The Health Care Center Application is a web-based tool that helps users identify diseases based on their symptoms and provides detailed information and recommendations.
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.
Recommending Recipes with Content-based Filtering Approach (based on nutritions)
2024-1 Machine Learning-based Data Analysis Final Team Project | 여행지 분위기 기반 향수 추천 시스템: Don't PERget Me
Chat-based music recommendation tool
Python SDK for Rumo API
Best Practices on Recommendation Systems
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
Bemore is a web application that helps you to keep up with the latest research in your field.
RecTools - library to build Recommendation Systems easier and faster than ever before
This repository offers a comprehensive suite of models for building a robust movie recommendation system. It explores various recommendation techniques including collaborative filtering, content-based filtering, and matrix factorization. Each approach is designed to enhance the user experience by providing personalized movie suggestions. Detailed d
A project that retrieves daily information from arXiv and recommends papers tailored to the user's preferences using Slack and Notion as the UI.
Final project of Web Technologies course. Electronic components stock manager for MMR Driverless Team.
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