Statistical Machine Intelligence & Learning Engine

Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)

Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)

Comparison-based Machine Learning in Python

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"

Experiments in NLOS mitigitation under MDS-based RF Positioning

Extendible metric MDS in Python

The code for Multidimensional Scaling (MDS), Sammon Mapping, and Isomap.

This routine is implemented in Matlab

This module allows users to analyze k-means & hierarchical clustering, and visualize results of Principal Component, Correspondence Analysis, Discriminant analysis, Decision tree, Multidimensional scaling, Multiple Factor Analysis, Machine learning, and Prophet analysis.

Simplified 3D DIffusion Model Simulation for Organization of Programming Languages Fall 2022.

Quadratic Programming with Complementarity Constraints

App for fast NMDS plots

Analyzing the historical cryptocurrency trading dataset, to portrait its dynamic landscape and dig into features of crypt currencies to figure out if any patterns in their price movement.

Dan McLinden

Performing Multidimensional Scaling with Gradient Descent and Gauss-Newton in JavaScript

PCA and MDS analyses

This repo contains project(s) from the Marketing Analytics course.

Explore spaces of phylogenetic trees

Performing common visual data analytic tasks using Python and D3.js.