Linear Algebra with Python is designed to provide a comprehensive refresher on the essential concepts of linear algebra, tailored for professionals and students in fields such as statistics, econometrics, quantitative analysis, and data science. Whether you're a seasoned expert or someone looking to solidify your foundational knowledge, this guide offers an in-depth exploration of critical topics in linear algebra, enriched with Python-based computation and visualization.
Throughout this book, we will delve into key concepts that are pivotal for advanced quantitative skill sets, including linear combinations, vector spaces, linear transformations, eigenvalues and eigenvectors, diagonalization, singular value decomposition, and more. Each concept is carefully explained and demonstrated with Python, making abstract ideas more concrete and applicable to real-world scenarios.