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 assistance of Python computation and visualization.

Selected Machine Learning algorithms for natural language processing and semantic analysis in Golang

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

This repository explores the variety of techniques and algorithms commonly used in machine learning and the implementation in MATLAB and PYTHON.

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

Fast truncated singular value decompositions

Julia code for the book Numerical Linear Algebra

Randomized Dimension Reduction Library

Digital Image Watermarking Method Based on Hybrid DWT-HD-SVD Technique: Attacks, PSNR, SSIM, NC

Official Code for "EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting (ICCV 2023)"

😎 A curated list of tensor decomposition resources for model compression.

Randomized Matrix Decompositions using R

Building Recommendation Model for the electronics products of Amazon

A SciPy implementation of "GraRep: Learning Graph Representations with Global Structural Information" (WWW 2015).

Implementing Content based and Collaborative filtering(with KNN, Matrix Factorization and Neural Networks) in Python

This repository contains lecture notes and codes for the course "Computational Methods for Data Science"

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

Demonstration of low rank matrix approximations via singular value decomposition

A course on Linear Algebra using Python in Jupyter notebooks

Building recommender systems in Julia

An introduction to matrix factorization and PCA and SVD.

Solve many kinds of least-squares and matrix-recovery problems

Jupyter notebooks (Python) for the course 3M1 at the Department of Engineering, University of Cambridge

Pytorch extension for Singular Value Decompostion (SVD) with LAPACK gesvd backend

Movie Recommendation System created using Collaborative Filtering (Website) and Content based Filtering (Jupyter Notebook)

A linear algebra library that provides a user-friendly interface to several BLAS and LAPACK routines.

Shiny App for Image Compression via SVD

:earth_asia: MH1DMT is inversion software using LM (Levenberg-Marquardt), SVD (Singular Value Decomposition), SA (Simulated Annealing), VFSA (Very Fast Simulated Annealing), and MVFSA (Modified Very Fast Simulated Annealing) of one-dimension magnetotellurics (MT) in MATLAB

MoMA: Modern Multivariate Analysis in R