The DGUT 2023 Linear Algebra SVD (Singular Value Decomposition) Recommendation 1.ipynb file is a Jupyter Notebook document focusing on the field of linear algebra. This document covers content related to Singular Value Decomposition in the context of the 2023 Linear Algebra course at Dongguan University of Technology. Singular Value Decomposition is a widely used technique in linear algebra and numerical analysis, allowing the decomposition of a matrix into the product of three matrices. This technique is significant in areas such as data dimensionality reduction and feature extraction. The Recommendation 1.ipynb file may contain specific instances, examples, or code to help students better understand and apply Singular Value Decomposition in linear algebra. Through a thorough study of this document, students can gain a deeper understanding of the theory and practical applications of linear algebra.