This projects focusses on PCA based Statistical Visualization for multivariate large data sets. Popular methods for visualizing PCA transformations are performed in R.
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Updated
Feb 11, 2014 - R
This projects focusses on PCA based Statistical Visualization for multivariate large data sets. Popular methods for visualizing PCA transformations are performed in R.
Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree
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
Customer Segments - Machine Learning Nanodegree from Udacity
Interactive data visualizations for Kaggle Brooklyn Home Sales data, built using D3.js
Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments
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 Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor
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.
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"
Text Mining and Analysis with Biplots.
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?
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.
Package for conducting PCA incl. scree-plot and bi-plot
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!"
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