knn-algorithm

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...

Go to: https://github.com/alexklibisz/elastiknn

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.

This repository is part of a course on Elasticsearch in Python. It includes notebooks that demonstrate its usage, along with a YouTube series to guide you through the material.

Efficient approximate k-nearest neighbors graph construction and search in Julia

Web application for engineering students to predict appropriate job roles using Machine learning and other guidance material like job descriptions, links to courses, etc.

Implementation of KNN algorithm in Python 3

机器学习算法实现及实战

A pure Python-implemented, lightweight, server-optional, multi-end compatible, vector database deployable locally or remotely.

Data Science Python Beginner Level Project

A simple framework for gesture recognition in Java

Train, evaluate, and optimize implicit feedback-based recommender systems.

Serverless, lightweight, and fast vector database on top of DynamoDB

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."

For Pancake Pridction, Try to use the machine learning algorithm KNN to predict it.

simple implementation of machine learning algorithm in pyhton

Traffic Congestion Prediction System using Data Mining

A look-alike model to identify potential clients based on certain characteristics from the existing customer base.