Includes top ten must know machine learning methods with R.

Scikit-Learn compatible HMM and DTW based sequence machine learning algorithms in Python.

This repository contains the Iris Classification Machine Learning Project. Which is a comprehensive exploration of machine learning techniques applied to the classification of iris flowers into different species based on their physical characteristics.

Fault diagnosis of some critical and non-critical faults in electric drives using anomaly detection.

An Open MPI implementation of the well known K-Nearest Neighbors (Machine Learning) classifier.

Just a simple implementation of K-Nearest Neighbour algorithm.

PCA(Principle Component Analysis) For Seed Dataset in Machine Learning

Syracuse University, Masters of Applied Data Science - IST 707 Data Analytics

This project involves detecting iris species using the k-nearest neighbors (KNN) algorithm in Jupyter Notebook. The iris species detection task is a classic problem in machine learning, where the goal is to classify iris flowers into different species based on their measurements.

This project is using Strava's API to download and process my workout data.

This project focuses on predicting heart disease using the K-Nearest Neighbors (KNN) classification algorithm implemented in a Jupyter Notebook. It aims to provide a tool that can assist in early detection and diagnosis of heart disease based on given input features.

Fraud detection

This is a Python - based application that predicts diseases based on the symptoms inputted by the user using machine learning (KNN classifier algorithm).

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.

k-Nearest Neighbors Algorithm with p-adic Distance

Static and Dynamic Analysis of android malware using various different machine learning algorithms

Portfolio

I contributed to a group project using the Life Expectancy (WHO) dataset from Kaggle where I performed regression analysis to predict life expectancy and classification to classify countries as developed or developing. The project was completed in Python using the pandas, Matplotlib, NumPy, seaborn, scikit-learn, and statsmodels libraries. The r…