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

k-Nearest Neighbors Algorithm with p-adic Distance

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 (KNN) used for an Etherium Blockchain classification problem

Aplicação web onde você consegue treinar um modelo de Machine Learning para classificar uma pessoa como do sexo masculino ou feminino com base em seu nome.

Performing comparative sentiment analysis to determine public reaction on newly introduced Farm Laws of 2020, India by collecting data using Twitter Tweepy API

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

This project was developed for the CSC-481: Artificial Intelligence class at Southern Connecticut State University. The purpose of this assignment was to use the K-Nearest Neighbor classifier, as well as Decision Tree classifier, to create AI models that could identify the gender of an individual from the provided face dataset.

A digit recognition program which allows digits to be drawn by the user.

Raw Coding Implementation Of Different Sorts Of Machine Learning Algorithms Without Using Library

Simpsons Members Recognizer Supervised Machine Learning Algorithm.

Rainfall Prediction Classifier for Australia using multiple classifier models.

Unsupervised Learning Algorithms being implemented to detect a liar.

Differentiates between single and binary star systems using photometric constraints and a k-NN classification algorithm.

A Python project that categorizes Spotify tracks into four moods based on their respective features.

Using Collaborative Filtering predicting Movie Rating and K-nearest Neighbours & SVM algorithms for Number ClassificationNumber Classification

4 machine learning models applied to 2 seperate binary classification problems each. These models include decision trees, neural networks, random forest bagging, and k-nearest neighbor.

Homework Anomaly Detection (AD), MSc Optional, Year 1, Semester 1, Faculty of Mathematics and Computer Science, University of Bucharest

This project focuses on classifying handwritten digits (0-9) using the K-Nearest Neighbors (KNN) algorithm implemented from scratch using Numpy and Matplotlib only.