Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
The recommender-engine, AI powered route generator.
Machine learning papers
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.
Pytorch domain library for recommendation systems
ai: basic movie recommender system
Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
Using the MovieLens dataset, will create a customer recommendation system from scratch using PyTorch.
An application that allow the user to log in (and access to all his data), and connect to external distributors, in order to get the coffee generated by a Machine Learning algorithm
In this project I am implement the simple Recommendation System using Python Programming language that suggests item to users based to their preferences. I use the techniques like collaborative filtering or content-based filtering to recommend movies, books or products to the users.
An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀
Image-based furniture recommendation system for better product discovery.
RecTools - library to build Recommendation Systems easier and faster than ever before
Python framework to extract multimodal features for multimodal recommendation in a highly-customizable way.
This is a book recommendation system based on item-based Collaborative Filtering memory-based model created using Flask.
Application that uses Spotify's API and a Content Filtering Model to recommend new songs that might appeal to the user.
The FranKGraphBench is a Framework to allow KG Aware RSs to be benchmarked in a reproducible and easy to implement manner. It was first created on Google Summer of Code 2023 for Data Integration between DBpedia and some standard RS datasets in a reproducible framework.
Recent Sony RISE Research Team India organized and this is my Solution in which I secured 3rd Position. Recommender systems are among the most popular applications of data science today. They are used to predict the "rating" or "preference" that a user would give to an item. In this Challenge I have computed and extracted several Features in ord…
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