A native JavaScript port of Google's S2 Geometry library

Plain python implementations of basic machine learning algorithms

10-315 Final Project

Testing face recognition power of different algorithms on ORL database.

The k-NN tool is to provide a generic tool to conduct k Nearest Neighbour (k-NN) prediction of continuous forest target variables of interest. In the context of Ecosystem Restoration monitoring, the tool allows wall-to-wall propagation of the variables of interest using field reference data and provided EO datasets. Part of the PEOPLE-ER project.

Welcome to my Classical Learning Projects repository, where I showcase my work in the fields of supervised and unsupervised learning. Here, you'll find code and datasets for various projects, such as classification and clustering tasks, implemented using popular algorithms like decision trees, neural networks, and k-means.

The question-answer paper discusses Data Science Algorithms (k-NN classifier & Naive Bayes classifier)

Simpsons Members Recognizer Supervised Machine Learning Algorithm.

Labs for the "Statistical Learning and Neural Networks" course @ Polytechnic University of Turin

Audio Pattern Recognition project - Music Genre Classification

Implementing k-NN algorithm with numpy

Projeto desenvolvido durante a disciplina SIN 492 - Reconhecimento de Padrões, da Universidade Federal de Viçosa - Campus Rio Paranaíba.

Built a voice-controlled car from scratch incorporating machine learning methods such as the Euclidean Classifier and k-NN Classifier, open and closed loop feedback control systems, principal component analysis, regression analysis, and transient analysis

This repository is used for "Computer Vision and Pattern Recognition" course work.

Trabajo Práctico de la materia Laboratorio de Datos sobre un Modelo de Regresión para predecir viajes diarios en EcoBici y un Clasificador de noticias reales y falsas de un dataset

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

This machine learning initiative seeks to leverage the k-Nearest Neighbors (k-NN) classification algorithm to predict whether a Universal Bank will accept a personal loan offer.

BigData Analysis - Breast Cancer Wisconsin Dataset (R, PCA, Machine Learning, ggplot2, dplyr): Exploring Kaggle's 'Breast Cancer Wisconsin (Original)' dataset. Objective: Develop a classification algorithm for benign/malignant tumor detection using PCA for dimensionality reduction and k-NN for classification. Achieved over 95% data retention.

Nearest neighbor search. Methods: LSH, hypercube, and exhaustive search. C++