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/
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Updated
Nov 11, 2024 - Rust
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/
A simple python OCR engine using opencv
Implementation of basic ML algorithms from scratch in python...
A novel Clustering algorithm by measuring Direction Centrality (CDC) locally. It adopts a density-independent metric based on the distribution of K-nearest neighbors (KNNs) to distinguish between internal and boundary points. The boundary points generate enclosed cages to bind the connections of internal points.
A pure Python-implemented, lightweight, server-optional, multi-end compatible, vector database deployable locally or remotely.
Efficient approximate k-nearest neighbors graph construction and search in Julia
机器学习算法实现及实战
Implementation of KNN algorithm in Python 3
A simple framework for gesture recognition in Java
Data Science Python Beginner Level Project
Web application for engineering students to predict appropriate job roles using Machine learning and other guidance material like job descriptions, links to courses, etc.
Train, evaluate, and optimize implicit feedback-based recommender systems.
Serverless, lightweight, and fast vector database on top of DynamoDB
Traffic Congestion Prediction System using Data Mining
This project is a reference implementation of the Hierarchical Navigable Small World graph paper by Malkov & Yashunin (2018) as a companion to the AWS presentation by Ben Duncan (Startup Solution Architect) "What you need to know about Vector Databases. From use-cases to a deep dive on the technology."
simple implementation of machine learning algorithm in pyhton
A look-alike model to identify potential clients based on certain characteristics from the existing customer base.
A casestudy about K-nearest-neighbors Algorithm
For Pancake Pridction, Try to use the machine learning algorithm KNN to predict it.
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