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knn-algorithm
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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.
Efficient approximate k-nearest neighbors graph construction and search in Julia
Implementation of KNN algorithm in Python 3
Web application for engineering students to predict appropriate job roles using Machine learning and other guidance material like job descriptions, links to courses, etc.
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.
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.
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."
Traffic Congestion Prediction System using Data Mining
A casestudy about K-nearest-neighbors Algorithm
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.