Learning

Linear Algebra for Machine Learning

Vectors and Vector Spaces → Applying Linear Algebra to ML Projects

This learning path equips data science and AI students with the linear algebra foundations needed to understand and apply core machine learning techniques. Starting from vector spaces and matrix operations, it progresses through matrix factorizations, SVD, PCA, and culminates in applications to regression and neural networks, with practical programming exercises throughout.