Coursera
Dive into the final chapter of our Linear Algebra Specialization series where you'll explore the intricate world of orthogonality and diagonalization. This course is designed to equip you with advanced knowledge on orthogonal vectors, transformation, and symmetric matrices, essential for a wide range of applications from engineering to data science.
Coursera
Dive into the essential mathematics behind one of the most popular dimensionality reduction techniques in machine learning: Principal Component Analysis (PCA). This comprehensive course is designed for those with an intermediate understanding of statistics and linear algebra, aiming to equip you with the skills needed to apply PCA effectively in your data science projects. By the end of this course, you'll have a solid grasp on how to minimize reconstruction error and extract meaningful patterns from high-dimensional datasets.
EdX
Dive into the complex world of Linear Algebra with this comprehensive course. Learn about Orthogonality & Symmetric Matrices and the Singular Value Decomposition (SVD) – essential topics that underpin many areas of mathematics, computer science, and engineering. This course is ideal for those looking to enhance their understanding of advanced linear algebra concepts.
EdX
Refresh your knowledge or learn from scratch about vectors, matrices, and linear equations with this beginner-friendly linear algebra course. Designed for students and professionals seeking a strong mathematical foundation, this course will equip you with the necessary skills to tackle more advanced topics in various fields such as physics, computer science, and engineering.