K Nearest Neighbors classifier from scratch for image classification using MNIST Data Set.

K means clustering for breast-cancer-wisconsin.data from scratch

This repository contains a Python implementation of a K-Nearest Neighbors (KNN) classifier from scratch. It's applied to the "BankNote_Authentication" dataset, which consists of four features (variance, skew, curtosis, and entropy) and a class attribute indicating whether a banknote is real or forged.

[With @HuangPatrick16777216] My distribution of KentOS, the random, open-source, forked-too-many-times, definitely-not-based-on-KentoNishi's-README-page OS. Read the DONTREADME.md for more info.

A project which uses machine learning K-Clustering to identify the likings and dislikings of a customer on based on their behaviour and analysis

Machine Learning ve Python: A'dan Z'ye Makine Öğrenmesi

I implemented the K-Means Clustering Model to Analyse the Data in Python and R

Movie Recommender API: FastAPI-based backend for movie recommendations using collaborative filtering.

python PWD gen

Jupyter kernel for the Goal array programming language

The project is mainly to demonstrate the performance in terms of convergence for Random Initialisation and K++ for K-Means Algorithm.

Created a correlation matrix to find important elements impacting institution rankings after doing extensive data investigation and cleaning to guarantee data accuracy and consistency and K-means clustering was used to find the best universities, giving stakeholders useful information.