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See Theory of Statistical Learning for a framework for analyzing and understanding the process of learning from data. Machine learning is the application of this theory to build practical systems that can learn and make predictions from data.

See Theory of Deep Learning for further mathematical foundations to Deep Learning. Here, I present the mathematical foundations and applications of such structure, methods, and operations that create the framework of Machine Learning Theory and allows such theory to be implemented in programming and applied to various of applications.

Linear Algebra

System of Linear Equations

Matrices

Solving Systems of Linear Equations

Vector Spaces

Linear Independence

Basis

Rank

Linear Mappings

Affine Spaces

Analytical Geometry

Norms

Inner Products

Length and Distances

Angles and Orthogonality

Orthonormal Basis

Orthonormal Complement