This repository contains two implementations of a K-Nearest Neighbors (KNN) classifier for predicting online shopping behavior. The classifiers are implemented in Python and use different approaches for finding the nearest neighbors: Naive Implementation, KDTree Implementation

A quantum version of KNN algorithm

This Repository consists of algorithms related to AI-ML. Few examples include - KNN, Naive Bayes, Decision Trees, etc.

This project classifies images from the Flower102 dataset using k-means clustering followed by K-Nearest Neighbors (KNN) classification. It optimizes KNN parameters to achieve high accuracy, with the best results obtained using 7 clusters and 5 nearest neighbors.

Titanic Dataset KNN Algorithm - Confusion Matrix

A time series classification challange. The point is to classifiy whether a child's handwriting is affected by dysgraphia. the features represent the movements of a pen on a tablet the child wrote on.

Predicting Hepatocellular Carcinoma through Supervised Machine Learning

This code loads network data, preprocesses it, reduces dimensions with an autoencoder, and trains multiple classifiers (KNN, RF, LR, SVM) for anomaly detection.

This repository aims to solve the captcha image on Fubon E-bank website

Using R Markdown for Data Analysis, Machine Learning

Desenvolvimento de um pipeline de machine learning para o conjunto de dados de pacientes com Carcinoma Hepatocelular (HCC) de modo a prever a sobrevivência dos pacientes 1 ano após o diagnóstico.

This project analyzes employee attrition data to uncover key factors, predict turnover, and develop strategies for retention, ultimately enhancing organizational stability and performance.

To build a classification system to predict whether a customer will churn or not based on the IBM Telecom Data from Kaggle. Technically, it is a binary classifier that divides clients into two groups-those who leave and those who do not. The classifier will be built using bagging algorithms like Random Forest, boosting algorithms & Neural Networks

Transaction classification: KNN, LR and NN

This repository contains a project demonstrating the implementation and application of the K-Nearest Neighbors (K-NN) algorithm in Data Science. The objective is to provide a comprehensive understanding of the K-NN algorithm, including data preprocessing, model training, evaluation, and visualization of results. This project is ideal for beginners

Classification of heart diseases with different artificial intelligence models

Python files employed in my research

R markdown files employed in my research