Popular GitHub Repositories for Knn

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/

Machine learning, in numpy

Gorse open source recommender system engine

Postgres with GPUs for ML/AI apps.

Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

JVector: the most advanced embedded vector search engine

Collections of vector search related libraries, service and research papers

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

A curated list of Best Artificial Intelligence Resources

GUI based Smart Sudoku Solver that tries to extract a sudoku puzzle from a photo and solve it

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

PostgreSQL vector database extension for building AI applications

Blazing fast framework for fine-tuning similarity learning models

Voice Conversion With Just Nearest Neighbors

An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.

A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈 出品

PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT

This repository contains the code which can recognise the alphabets in Indian sign language for blind using opencv and tensorflow.

This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms