Collection of Code used in Articles for Coffee and Data Science

Principal Component Analysis of surfaces, i.e. functions defined on a bivariate domain.

The data at hand is of flight satisfaction survey along with the customer flight information, the task at hand is to build a model that predicts satisfaction/dissatisfaction given the various attributes

PCA-based clustering of student grades to explore academic performance patterns (R)

This repository contains the R scripts and data for an automated PCA of the gravier dataset

🧬 Automated single-cell RNA-seq analysis pipeline with R/Seurat. Features adaptive QC, clustering, DE analysis, and publication plots. Handles real NCBI data with intelligent fallbacks. Zero-configuration, publication-ready results.

The objective of the project is to use the dataset to build a regression model to predict satisfaction. Project Approach, Data Exploration, Collinearity of the variables ,Initial Regression analysis Factor Analysis, Labeling and interpreting of the factors, Regression analysis using the factors as independent variable, Model performance measures

Face recognition via PCA and KNN

PCA is a statistical technique for reducing the dimensionality of a dataset

R package for Co-Kurtosis PCA.

Multivariate Statistics Project

Public data for the Embedding Projector

Trabalhos de Inteligência Computacional Aplicada

Factor Analysis/ PCA , t- test , hypothesis testing

Re-sampled dimensional reduction (RSDR)

A no-nonsense introduction to Shiny for researchers, clinicians, statisticians, and scientists of all varieties, with a focus on interactive reports and re-usability.