Singular Value Decomposition (SVD) on Julia
Автор: Nazmus Sakib Pallab
Загружено: 2025-10-02
Просмотров: 9
Описание:
Hello everyone, I explored Singular Value Decomposition (SVD) and its applications in image analysis.
We learned how SVD decomposes data into three parts:
𝑈, Σ, and 𝑉(T)
Using SVD, we applied face image reconstruction and low-rank approximations.
This method helps in dimensionality reduction, image compression, and Eigenface analysis.
It was exciting to see how math directly connects to real-world applications in facial data!
Please checkout the links to my other videos on Julia:
1. Introduction to Image Processing: " • Julia Basics on Image Manipulation "
2. Data Wrangling: " https://fb.watch/CujcfY_cus/ "
#SingularValueDecomposition #MachineLearning #DataScience #Eigenfaces #ImageCompression #MathematicsInAction #JuliaLang #ComputerVision #LowRankApproximation #DimensionalityReduction
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