Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering

Repository for Udemy Course: Identify problems with Artificial Intelligence

An implementation of K-Means algorithm in R

Image Segmentation using Superpixels, Affinity Propagation and Kmeans Clustering

Animated Visualizations of Popular Machine Learning Algorithms

An R package that produces a tidy output for kmeans and linear regression models evaluation!

Imagine you are the front runner for democratic party primaries in 2008 - 1 week into elections you have won a few states(Obama) and your opponent (Hillary) is catching up. How you can use analytics to predict which of the remaining seats will you win using demographic data from states you won and lost. Can we accurately classify win or lose for…

R exercises (2016)

An Analisys of customers with R program language.

It's a package containing functions that allow you to create your own color palette from an image, using mathematical algorithms

Comparison of kmeans and supercells for image semgentiation 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 project implements canonical correlation analysis between two data matrices. I first create the latent dimensions between the two data matrices. Then I use Kmeans and hierarchical clustering on principal component to group individuals using the latent dimensions and the distance created by the canonical analysis. Last step, I give a profili…

Cluster analysis - using different approaches

The feature of interest is whether or not a customer buys a caravan insurance, based on socio-demographic factors and ownership of other insurance policies; and to build profile of a typical customer.

Final project for the subject Data Mining I of my MsC.

Data Science in R (multiple algo`s)

K-means clustering algorithm to group people who live close to each other.

Classify the subsidy eligible users based on their electricity usage patterns

Worked on building a predictive model by considering multicollinearity and other Machine learning concepts related to  factors or variables using R programming.