Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Repository Index
47,133 repositories indexed
1–18 of 18 · Most stars
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Best Practices on Recommendation Systems
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.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
A Python scikit for building and analyzing recommender systems
A Python implementation of LightFM, a hybrid recommendation algorithm.
A unified, comprehensive and efficient recommendation library
Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
Fast Python Collaborative Filtering for Implicit Feedback Datasets
Accelerated deep learning R&D
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
fastFM: A Library for Factorization Machines
A library of metrics for evaluating recommender systems
Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
A C library for product recommendations/suggestions using collaborative filtering (CF)
Exploit black-box recommenders for algorithm selection.