Statistical Machine Intelligence & Learning Engine
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Updated
Nov 5, 2024 - Java
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 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.
Unsupervised Learning
Analysis of Data Scientist Job Descriptions using Natural Language Processing
This routine is implemented in Matlab
Module for Niek Veldhius, Sumerian Text Analysis.
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.
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"
Using R & VoteView mutlidimensional scaling (MDS) methods for the analysis & visualization of complex patterns of crosslinguistic variation.
The code for Multidimensional Scaling (MDS), Sammon Mapping, and Isomap.
Experiments in NLOS mitigitation under MDS-based RF Positioning
Showcasing Manifold Learning with ISOMAP, and compare the model to other transformations, such as PCA and MDS.
Extendible metric MDS in Python
A library for the Analysis of Molecular Dynamics Simulations of Self Assembling Peptides. Started during an internship at CNTE, Niguarda Hospital, Milan
Collective Project is one of our required courses for master degree in Mathematics which comprises of 5 members each. In this our group, we are working on Multidimensional Scaling: Multidimensional Scaling is a set of procedures that allows the researcher to map distances between objects in a multidimensional space into a lower-dimensional space…
Multidimensional Scaling using Cliques (MDS-Clique)
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