In this post, we will explore the use of SVD on Image analysis. We will mainly use SVD on images to get main components/singular vectors capturing the image and use part of them to reconstruct the image. Singular Value Decomposition (SVD) is one of the commonly used dimensionality reduction techniques. SVD/PCA is the mainstay of… Continue reading Image Reconstruction using Singular Value Decomposition (SVD) in Python
Category: SVD in Python
Singular Value Decomposition (SVD) in Python
Matrix decomposition by Singular Value Decomposition (SVD) is one of the widely used methods for dimensionality reduction. For example, Principal Component Analysis often uses SVD under the hood to compute principal components. In this post, we will work through an example of doing SVD in Python. We will use gapminder data in wide form to… Continue reading Singular Value Decomposition (SVD) in Python