Linear Algebra Fundamentals for Machine Learning
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Updated
Aug 20, 2019 - Jupyter Notebook
Linear Algebra Fundamentals for Machine Learning
This repository contains the implementations of the MUSIC and ESPRIT algorithms, which can be used for super-resolution spectral analysis.
Statistical Shape Model using PCA on standard 2D hand dataset
Official code repository for "Distribution-Independent Confidence Intervals for the Eigendecomposition of Covariance Matrices via the Eigenvalue-Eigenvector Identity" (ICML 2021 Workshop on Distribution-Free Uncertainty Quantification).
A Step-by-step tutorial to implement PCA.
A matlab tool that analytically calculates the transient Electromigration (EM) stress at discrete spatial points in multi-segment lines of power grids.
ECCV22 "Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality" and T-PAMI extension
Julia code for the book Numerical Linear Algebra
ECCV22 Paper "Batch-efficient EigenDecomposition for Small and Medium Matrices"
Implementation of a Speaker Recognition Algorithm using MFCC, FFT, and Eigendecomposition from voice samples
Differentiable matrix factorizations using ImplicitDifferentiation.jl.
Jupyter notebooks with notes, code, and exercises from Linear Algebra: Theory, Intuition, Code by Mike X Cohen (2021).
Application of PCA in facial recognition
practical linear algebra for data science (with python)
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