國立清華大學 數學系

This presentation provides a concise overview of applied linear algebra, emphasizing its real-world problem-solving capabilities. We will explore the fundamental concepts of vectors, matrices, and linear systems, focusing on the least-squares method and its wide-ranging applications. Through data fitting, classification, control, and estimation examples, we will demonstrate how linear algebra enables us to extract insights from data, make predictions, and design optimal systems. We will also highlight the essential role of programming in applying these techniques, showcasing examples using popular tools like Python and Julia. This presentation aims to equip attendees with a solid understanding of applied linear algebra's core principles and its potential to address challenges across diverse fields.