Fast k-Nearest Neighbors Classifier for Large Datasets

Animated Visualizations of Popular Machine Learning Algorithms

A document covering machine learning basics. 🤖📊

Cryptocurrency market cap-price prediction and visualization web app

Pixel based classification of satellite imagery - feature generation using Orfeo Toolbox, feature selection using Learning Vector Quantization, CLassification using Decision Tree, Neural Networks, Random Forests, KNN and Naive Bayes Classifier

Kernel k Nearest Neighbors in R

Archived repo (see Readme) - R package for regression and discrimination, with special focus on chemometrics and high-dimensional data.

Archived repo - This R Package is not developed anymore (only maintenance). It was replaced by R package rchemo

Chatbot developed in R Shiny using 2 KNN models for classification with Caret library.

R codes for common Machine Learning Algorithms

A collection of problems solved with machine learning algorithms, using R.

Retaining key employees is a major stake for any organization but are there reliable ways to figure out if and why the best and most experienced employees are leaving prematurely? Most firms these days are already integrating the benefits of using analytics to introduce special efforts in retaining employees as well as in hiring decisions. Lot o…

Implementation of k-Nearest Neighbours algorithm for use on geometric morphometric data and a simulated dataset.

Eigenfaces and Fisherfaces for Face Recognition. With implementation of algorithms as PCA, KNN, Fisher Discriminant Analysis.

Feature engineering in machine learning

Classic Machine Learning in R

Designing and applying unsupervised learning on the Radar signals to perform clustering using K-means and Expectation maximization for Gausian mixture models to study ionosphere structure. Both the algorithms have been implemented without the use of any built-in packages. The Dataset can be found here: https://archive.ics.uci.edu/ml/datasets/ion…

This app is intended to dynamically integrate machine learning techniques to explore multivariate data sets.

Machine Learning exercises for my subject of Machine Learning at University of Granada (UGR).