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 offers a complete K-Nearest Neighbors (KNN) tutorial, guiding you from core theory to hands-on practice. Learn to implement KNN from scratch with NumPy, apply it using scikit-learn, and explore visualizations, datasets, and Jupyter notebooks to fully understand, test, and optimize the algorithm.

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

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.

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

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…

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.

k-Nearest Neighbors Algorithm with p-adic Distance

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).

Data Science Project: SpaceX Falcon 9 First Stage Landing Prediction.

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.