eigenvalues-and-eigenvectors

Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

Three C++ projects assigned for the Numerical Methods for Electrical Engineering (EE 242) course in the Spring 2021 semester.

The code for generalized eigenvalue problem

A library providing modules with easy to use matrix operations for real(8) and complex(8) arrays

Imperial College London »Mathematics for Machine Learning«. A sequence of 3 courses on the prerequisite mathematics for applications in data science and machine learning. (1) Linear Algebra (2) Multivariate Calculus and (3) Principal Component Analysis (completed Sept. 10th, 2018)

This is official github repo for CVPR2026 Main Track paper "ERMoE: Eigen-Reparameterized Mixture-of-Experts for Stable Routing and Interpretable Specialization"

Linear Algebra Step by Step by Kuldeep Singh. Solved step by step through LaTeX

Passenger Flow Optimisation in the Singapore MRT network through Linear Algebra, Monte Carlo Simulation, Dijkstra's Algorithm, Graph Theory and Pareto Frontier Optimisation

Polynomial filtering eigensolver and Hamiltonian tools for quantum many-body simulations in Julia.

Fast, numerically-stable pure Lean 4 closed-form floating-point eigensolver of real 3x3 symmetric matrices

ForEig - A Fortran library for eigenvalue and eigenvector calculations.

Somos Agustín Demarco y Nazareno Rodríguez. Ambos somos ayudantes de la materia Álgebra y Geometría Analítica de la Universidad Tecnológica Nacional (Argentina), Facultad Regional Delta. Además, somos estudiantes de Ingeniería en Sistemas en la misma institución. Con el fin de que sea utilizada por nuestros alumnos, diseñamos esta calculadora.

Visualize linear algebra concepts.

Quantitative Finance Project utilizing mean-reversion and momentum applied to S&P 500 Stocks. Mean reversion factor found by taking an fPCA decomposition of returns from the S&P500 stocks.

Statistical Pattern Recognition: PCA and Bayesian Classifiers

Project written in C++ on basic simulations of eigenstates of the Hamiltonian in the One Dimensional Schrödinger Equation for common potential functions

Numerical solution of the time-independent Schrödinger equation using finite difference methods in Python. Active computational physics project.

A PyGame simulation of the motion over time for an interconnected mass-spring-system with n masses

The software is an implementation of the enriched subspace iteration method for solving the generalized eigenvalue problems.