Abstract Algebra Algebra Algebraic Geometry Algebraic Topology Applied Mathematics Arithmetic Geometry Basic Algebra Basic Mathematics Calculus Category Theory Classical Analysis Combinatorics Commutative Algebra Complex Algebra Complex Analysis Differential Algebra Differential Analysis Differential Calculus Differential Equations Differential Geometry Differential Topology Discrete Mathematics Elliptic Curves Fourier Analysis Functional Analysis Fractals Fractional Calculus Geometric Algebra Geometry Geometric Topology Groups Theory Graph Theory Harmonic Analysis Higher Algebra History of Mathematics Homological Algebra Integral Calculus K-theory Lie Algebra Linear Algebra Mathematical Analysis Mathematical Series Modern Geometry Multivairable Calculus Number Theory Numerical Analysis Probability Theory Real Analysis Rings and Fileds Riemannian Geometry Theorems in Calculus Topology Trigonometry Set Theory Constants & Numerical Sequences
Computational Mathematics for Learning and Data Analysis
This note aims at providing the mathematical foundations for some of the main computational approaches to Learning, Data Analysis and Artificial Intelligence. Topics covered includes: Topology and Calculus, Matrix products, Orthogonality and positive definiteness,Singular value decomposition, SIngular value decomposition, Matrix norms, Unconstrained Optimality and Convexity, QR factorization, Applications of linear least squares, Linear least squares: properties and normal equations, Pseudoinverse of a matrix, Linear least squares, Unconstrained Optimization.
Author(s): Antonio Frangioni and Federico Poloni
NA Pages 
Computational Mathematics An Introduction by I Liang Chern
This note explains the following topics: solving equations of one variable, Basic numerical linear algebra, Approximation theory, Numerical integration, Numerical ordinary differential equations.
Author(s): I Liang Chern, National Taiwan University
160 Pages
Introduction to Computational Mathematics by Greg Fasshauer
This note describes the following topics: Mathematical modeling, Taylor series, Floating point numbers and MATLAB.
Author(s): Greg Fasshauer, Illinois Institute of Technology
163 Pages
This lecture note covers the following topics: Prelude: computation, undecidability and the limits of mathematical knowledge, Computational complexity 101: the basics, Problems and classes inside N P, Lower bounds, Boolean Circuits, and attacks on P vs. NP, Proof complexity, Randomness in computation, Abstract pseudo-randomness, Weak random sources and randomness extractors, Randomness in proof, Randomness in proofs, Arithmetic complexity, Interlude: Concrete interactions between Math and Computational Complexity.
Author(s): Avi Wigderson
372 Pages
Introduction To Computational Mathematics
The goal of computational mathematics, put simply, is to find or develop algorithms that solve mathematical problems computationally. Topics covered includes: Errors and Error Propagation, Root Finding, Interpolation, Integration, Discrete Fourier Methods and Numerical Linear Algebra.
Author(s): H. De Sterck, P. Ullrich, Department of Applied Mathematics, University of Waterloo
118 Pages