Statistical and Algorithmic Investing Strategies for Everyone

Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assis…

Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.

LAPACK development repository

A header-only C++ library for large scale eigenvalue problems

V library to develop Artificial Intelligence and High-Performance Scientific Computations

Krylov methods for linear problems, eigenvalues, singular values and matrix functions

PReconditioned Iterative MultiMethod Eigensolver for solving symmetric/Hermitian eigenvalue problems and singular value problems

Rust Scientific Libary. ODE and DAE (Runge-Kutta) solvers. Special functions (Bessel, Elliptic, Beta, Gamma, Erf). Linear algebra. Sparse solvers (MUMPS, UMFPACK). Probability distributions. Tensor calculus.

C++ Matrix -- High performance and accurate (e.g. edge cases) matrix math library with expression template arithmetic operators

The Arnoldi Method with Krylov-Schur restart, natively in Julia.

A C++ library for solving second-quantized Hamiltonians

PyTorch implementation comparison of old and new method of determining eigenvectors from eigenvalues.

Nonlinear eigenvalue problems in Julia: Iterative methods and benchmarks

Numerical computation in native Haskell

R Interface to the Spectra Library for Large Scale Eigenvalue and SVD Problems

This Repository contains Solutions to the Quizes & Lab Assignments of the Mathematics for Machine Learning Specialization offered by Imperial College of London on Coursera taught by David Dye, Samuel J. Cooper, A. Freddie Page, Marc Peter Deisenroth

Pure Python implementation of the finite difference frequency domain (FDFD) method for electromagnetics

Autodiff is a numerical library for the Go programming language that supports automatic differentiation. It implements routines for linear algebra (vector/matrix operations), numerical optimization and statistics

codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"