pca: A Python Package for Principal Component Analysis.

A fast and scalable phylogenetic tree viewer for microbiome data analysis

manage ordinations and render biplots in a tidyverse workflow

Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree

This repository contains materials associated to the course "Multivariate Analysis" taught at the Faculty of Mathematics and Statistics (FME), UPC under the MESIO-UPC-UB Interuniversity Program under the instructors "Ferran Revertar", "Miguel Salicru" and "Jan Graffelman"

Worked with fellow peers at University of Pittsburgh under supervision of Dr. Junshu Bao, Department of Statistics, University of Pittsburgh, to do a Differential Gene Expression Analysis on a Dexamethasone treatment data set and incorporated Machine Learning into project.

VTubers as influencers might sound naive back then, but nowadays their presence is all around us. So, what are they?

Text Mining and Analysis with Biplots.

Interactive data visualizations for Kaggle Brooklyn Home Sales data, built using D3.js

Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor

Analysis of nutrient information from USDA National Nutrient Database using PCA

Package for conducting PCA incl. scree-plot and bi-plot

R script for creating beautiful biplots - all in base R, no other packages required.

Biplots, Volcano plots, PCA plots, Heatmaps and more Computational Genomics data created and visualized during University of Pittsburgh course, Computational Biology (BIOSC1540), with Dr. Miler Lee

Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments

Tutorial on creating an aesthetically pleasing PCA bipot in R.

This projects focusses on PCA based Statistical Visualization for multivariate large data sets. Popular methods for visualizing PCA transformations are performed in R.

Your one-stop solution for comprehensive genotype × environment interaction and stability analysis (AMMI model) using the metan package. Save time, perform analyses for all traits at once, and gain insightful visualizations effortlessly!"

StabilityApp: Stability Analysis App for Genotype by Environment Interaction (GEI) in Multi-Environment Trials

Apply unsupervised machine learning techniques on product spending data collected for customers of a wholesale distributor in Lisbon, Portugal to identify customer segments hidden in the data

The main goal of this project is to use various Clustering Methods for Bank Customer Segmentation.

Example of Biplot Graph using R

R package, creation of customizable biplots, both in two and three dimensions. Tested in Windows 7 and Mac OS X 10.9.5.

Your one-stop solution for comprehensive genotype × environment interaction and stability analysis (WAAS model) using the metan package. Save time, perform analyses for all traits at once, and gain insightful visualizations effortlessly!"

Tutorial code for performing PCA (with mathematical explanation) on breast cancer features computed from digitized images of fine needle aspirate (FNA) of a breast mass. Center the data, calculate correlation matrix, compute principal components, visualize and interpret results.

Customer Segments - Machine Learning Nanodegree from Udacity

Your one-stop solution for comprehensive genotype × environment interaction and stability analysis (GGE Biplot model) using the metan package. Save time, perform analyses for all traits at once, and gain insightful visualizations effortlessly!"

Exploratory Data Analysis using machine learning techniques as an exercise for GLY6932 (Data Science and Machine Learning Methods in the Geosciences) at the University of Florida.

genotype by trait PCA Bioplots