Fast k-NN graph construction for slow metrics

My first end-to-end project, using Web Scraping with BeautifulSoup and Spotify API. Clustering songs based on its audio features.

You Say "HI" , this program classifiies it .....

The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems

For this project, we'll be using a non-parametric classification method, k-nearest neighbors algorithm, to compress images.

recognize mouse-written numbers using KNN, Neural Network, and Convolutional Neural Network models

This GitHub repository hosts the project report and analysis code on investigating lifestyle habits and medical conditions influencing diabetes prevalence. Utilizing data from the CDC's Behavioral Risk Factor Surveillance System survey, the project explores correlations and predictive models for diabetes risk.

Performed Clustering Analysis using SAS v9.4 on Power Usage & Consumer Goods Data to draw insights about the dataset.

This is a Python repository implementing a K-Nearest Neighbors (KNN) algorithm for predictive modeling using car data.

This project creates an image of various points, with each pixel colored according to that pixel's distance to the nearest couple of points and their respective colors.

This repository contains the code for a K-Nearest Neighbors (KNN) model built to classify customer segments in Türkiye using the teleCust1000T dataset. The project includes data cleaning, visualization, feature scaling, model training, and evaluation with accuracy metrics.

Implementation of K-Nearest Neighbours (KNN) from scratch

A KNN algorithm based on the HVDM distance metric powered by decision trees using Weka libraries as a complement developed in Python.

This project aims to build a complete pattern recognition system to solve classification problems using the k-Nearest Neighbors (KNN) algorithm. To classify chest X-ray images into three categories: COVID-19 positive, pneumonia positive, and normal. To achieve this, we utilize the COVID-19 Chest X-ray dataset available on Kaggle.

Neural Network KNN for determining the state of the road surface

A complete Guide to K-Nearest-Neighbors with Applications in Python

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We test the algorithmic effectiveness of Monte Carlo Simulation, Temporal Difference Algorithm, and Dynamic Programming on a variant of shoots and ladders.

A fast and efficient K-Nearest Neighbors classifier implementation with three distance computation strategies (vectorized, one-loop, two-loop). Features CIFAR-10 dataset support, performance benchmarking, cross-validation for optimal k selection, and comprehensive documentation. Perfect for educational purposes and machine learning projects.

A simple python script that implements K Nearest Neighbors Algorithm. University Assignment

Konu: Kendi Belirlediğimiz bir problem için uzman sistem oluşturma

Samsun Innovation Campus 301 AI (HR Data Analysis ,Visualization and modelling)

This project uses the K-Nearest Neighbors algorithm to classify individuals into gender categories based on their physical attributes. It assesses the model's performance across different configurations and feature sets.