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Linear-Algebra-With-Python

weijie-chen / Linear-Algebra-With-Python

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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…

python data-science jupyter matrix linear-algebra mathematics data-visualization data-analysis eigenvectors computational-science vector-space matrix-calculations eigenvalues singular-value-decomposition diagonalization gram-schmidt linear-transformations null-space symmetric-matrices multivariate-normal-distribution
  • Updated Jan 13, 2023
  • Jupyter Notebook

pbenner / autodiff

Star 53

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

go golang statistics linear-algebra automatic-differentiation rprop special-functions linear-algebra-library numerical-optimization eigenvalues determinant statistical-models newton-raphson gauss-jordan bfgs singular-value-decomposition cholesky-decomposition gram-schmidt qr-algorithm hessenberg-reduction
  • Updated Dec 8, 2021
  • Go

shantanu1109 / Coursera-Imperial-College-of-London-Mathematics-For-Machine-Learning-Specialization

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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

linear-regression linear-algebra pagerank-algorithm neural-networks eigenvectors lagrange jacobian hessian backpropagation eigenvalues transformation-matrix newton-raphson taylor-series gram-schmidt sandpit multivariate-calculus
  • Updated Sep 23, 2023
  • Jupyter Notebook
parallel-PCA-openmp

arneish / parallel-PCA-openmp

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A parallelized implementation of Principal Component Analysis (PCA) using Singular Value Decomposition (SVD) in OpenMP for C. The procedure used is Modified Gram Schmidt algorithm. The method for Classical Gram Schmidt is also available for use.

c openmp parallel-computing pca-analysis pca svd principal-component-analysis qr-decomposition singular-value-decomposition gram-schmidt openmp-parallelization modified-gram-schmidt classical-gram-schmidt
  • Updated May 9, 2019
  • C

Vedant2311 / Numerical-Algorithms-Assignments

Star 1

Compilation of the assignments of the course of COL726: Numerical Algorithms (Spring 2021) and their solutions

numerical-methods iterative-methods conjugate-gradient gmres lu-decomposition singular-value-decomposition newton-method eigen-vector-decomposition cholesky-decomposition gram-schmidt floating-point-arithmetic floating-point-accuracy-problems qr-factorization broyden-method arnoldi-algorithm
  • Updated Jul 15, 2021
  • Python

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