Understand SVD | U, Σ, Vᵀ Explained | Solved Example | ML | Marathi

In this video, I have explained Singular Value Decomposition (SVD) in a simple and step-by-step way. If you are confused about how a matrix is broken into U, Σ, and Vᵀ, this video will help you understand the complete process with a solved example. Notes: https://drive.google.com/file/d/1Gb7-V204tFRGpvkUsRGuewQeN6W2gBz1/view?usp=sharing 📌 What you’ll learn: What is SVD (Singular Value Decomposition) Meaning of U, Σ, and Vᵀ matrices Step-by-step process to perform SVD Solved numerical example for better understanding Why SVD is important in Machine Learning SVD is widely used in Machine Learning, PCA, and data compression, so understanding this concept is very important.