Calculus by William E. Boyce and Richard DiPrima.

The Calculus - A Genetic Approach by Otto Toeplitz.

Introduction to Calculus and Analysis by Richard Courant and Fritz John.

A Course of Modern Analysis by E. T. Whittaker and G. N. Watson.

Ordinary Differential Equations by Edward L. Ince.

Div, Grad, Curl, and All That: An Informal Text on Vector Calculus by H. M. Schey.

Asymptotics and Special Functions by Frank W. J. Olver.

Nonlinear dynamics and chaos by Steven H. Strogatz.

LINEAR DIFFERENCE EQUATIONS by Kenneth S. Miller.

Difference Equations: An Introduction with
Applications by Walter G. Kelley and Allan C. Peterson.

Introduction to Linear Algebra by Gilbert Strang.

Fundamentals of MATRIX COMPUTATIONS by David S. Watkins.

A Multigrid Tutorial by D. Briggs

Matrix Computations by G. Golub and C. van Loan.

APPLIED LINEAR ALGEBRA: The Decoupling Principle by Lorenzo Sadun.

An Introduction to Multigrid Methods by Pieter Wesseling

Applications of Linear Algebra by Chris Rorres and Howard Anton

Matrices and Linear Transformations by Anthony J. Pettofrezzo.

A First Look at Numerical Functional Analysis by W. W. Sawyer

Numerical Methods that Work by Forman S. Acton

Numerical Computing With Matlab by Cleve Molder.

Finite-difference Equations and Simulations by Francis Begnaud Hildebrand.

Afternotes on Numerical Analysis by G. W. Stewart.

Numerical Methods Using Matlab by G. Lindfield and J. Penny

Numerical Methods in Engineering with Python by Jaan Kiusalaas

Introduction to Finite Mathematics by J. Kemeny, J. Snell, and G. Thompson.

An Introduction to Genetic Algorithms by Melanie Mitchell.

Practical Genetic Algorithms by Randy L. Haupt and Sue Ellen Haupt.

Numerical Optimization by J. Nocedal and S. Wright.

Optimum Seeking Methods by J. Wilde

Introduction to Linear Optimization by Dimitris Bertsimas and John N. Tsitsiklis.

An Introduction to the Method of Characteristics by Michael B. Abbott

Partial Differential Equations by Lawrence C. Evans.

Partial Differential Equations; Analytical Solution Techniques by J. Kevorkian.

Linear Integral Equations by Rainer Kress.

A Primer On Integral Equations of the First Kind by G. Milton Wing.

Nonlinear Partial Differential Equations for Scientists and Engineers by Lokenath Debnath.

**Ordinary**

Solving ODEs with MATLAB by L.F. Shampine, I. Gladwell, S. Thompson

**Partial**

Numerical Computation of Internal and External Flows: Volume 1 & 2 by C. Hirsch

The Finite Element Method: Basic Concepts and Applications by D. Pepper and J. Heinrich.

Finite Volume Methods for Hyperbolic Problems by Randall J. LeVeque.

Numerical Methods for Conservation Laws by Randall J. LeVeque.

Linear and Nonlinear Waves by Gerald Beresford Whitham.

Supersonic Flow and Shock Waves by Richard Courant.

Thermo-dynamics by Enrico Fermi.

Introduction to Thermal Physics by Daniel V. Schroeder

Statistical Physics by Gregory H. Wannier.

Fundamentals of Statistical and Thermal Physics by Frederick Reif.

Stress Waves in Solids by H. Kolsky.

Mathematical Models of Fluiddynamics: An Introduction by Rainer Ansorge.

Elementary Fluid Dynamics by D. J. Acheson.

Introduction to Wave Propagation in Nonlinear Fluids and Solids by Douglas S. Drumheller.

A First Course in Probability by Sheldon Ross.

Introduction to PROBABILITY MODELS: Seventh Edition by Sheldon M. Ross.

Applied Probability Models with Optimization Applications by Sheldon M. Ross.

An Elementary Introduction to Mathematical Finance by Sheldon M. Ross.

Introduction to Stochastic Models by Roe Goodman.

Basic Concepts of Probability and Statistics by J. L. Hodges and E. L. Lehmann.

The Mathematics of Financial Derivatives by P. Wilmott

Paul Wilmott on Quantitative Finance by P. Wilmott

Frequently Asked Questions in Quantitative Finance by P. Wilmott

Computational Finance Using C and C# by Georege Levy.

Statistics and Data Analysis for Financial Engineering by David Ruppert

Empirical Market Microstructure by Joel Hasbrouck.

An Introduction to Mathematical Statistics and Its Applications by Richard J. Larsen and Morris L. Marx. (Partial)

Methods and Applications of Linear Models: Regression and the Analysis of Variance by Ronald Hocking. (TBD)

Applied Linear Models with SAS by Daniel Zelterman.

Time Series Analysis: Forecasting and Control by George E. P. Box and Gwilym M. Jenkins.

Statistical Methods for Forecasting by Boyas Abraham and Johannes Ledolter.

Computational Statistics Handbook with Matlab by Wendy Martinez and Angel Martinez.

Exploratory Data Analysis with MATLAB by Wendy Martinez and Angel Martinez.

Reinforcement Learning: An Introduction by Richard Sutton and Andrew Barto

Approximate Dynamic Programming by Warren B. Powell

Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig

Pattern Recognition by Sergios Theodoridis and Konstantinos Koutroumbas

Pattern Classification and Scene Analysis (First Edition) by Richard Duda and Peter Hart

Pattern Classification (Second Edition) by Richard Duda, Peter Hart, and David Stork

The Elements of Statistical Learning by Jerome Friedman, Trevor Hastie, and Robert Tibshirani

An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani

Applied Predictive Modeling by Max Kuhn and Kjell Johnson

Statistical Learning from a Regression Perspective by Richard A. Berk

Data Analysis and Graphics Using R: An Example-Based Approach by John Maindonald and W. John Braun

Detection, Estimation, and Modulation Theory Part 1 Harry L. Van Trees.

Detection, Estimation and Classification:
An Introduction to Pattern Recognition and Related Topics by C. W. Therrien

Computer Approaches to Pattern Recognition by William S. Meisel.

Optimal Decision Theory by William DeGroot.

Optimal Control and Estimation by Robert F. Stengel.

Kalman Filtering Theory and Practice using MATLAB by Mohinder Grewal and Angus Andrews.

Applied Optimal Estimation edited by Arthur Gelb.

Classification, Parameter Estimation, and State Estimation by F. van der Heijden, R. P. W. Duin, D. de Ridder, and D. M. J. Tax.

Applied Linear Regression by Sanford Weisberg.

Residuals and Influence in Regression by R. Dennis Cook and Sanford Weisberg.

Probability and Statistics: For Engineering and the Sciences by Jay L. Devore

Resampling Methods: A Practical Guide to Data Analysis by Phillip Good

Pattern Recognition: A Statistical Approach by Pierre A. Devijver and Josef Kittler.

Basic Statistics: Understanding Conventional Methods and Modern Insights by Rand R. Wilcox.

Programming Collective Intelligence by Toby Segaran.

Introducing Monte Carlo Methods with R Christian P. Robert and George Casella.

Adaptive Filtering Primer by A. Poularikas and Z. Ramadan

Adaptive Filtering Theory by Symon Haykin

Principles of Adaptive Filters and Self-learning Systems by Anthony Zaknich.

Introduction to ALGORITHMS by T. Cormen, C. Leiserson, and R. Rivest.

Parallel Programming with MPI by Peter Pacheco

Introduction to Parallel Computing by Vipin Kumar, Ananth Grama, Anshul Gupta, & George Karypis.

Foundations of Multithreaded, Parallel, and Distributed Programming by Gregory R. Andrews

Unix Utilities by Ramkrishna S. Tare.

Learning Python by Mark Lutz & David Ascher.

Learning Perl by Randal L. Schwartz, Tom Phoenix, and Brian Foy.

THE ELEMENTS OF PROGRAMMING STYLE by Brian W. Kernighan and P. J. Plauger.

Street-Fighting Mathematics by Sanjoy Mahajan

Codes, Ciphers, and Secret Writing by Martin Gardner

The Contest Problem Books: Annual High School Mathematics Contests

Fantastic Book of Math Puzzles by Margaret Edmiston

Puzzles to Puzzle You by Devi Shakuntala

How Would You Move Mt. Fuji? and Are You Smart Enough to Work at Google by William Poundstone

Signals and Systems by Alan Oppenheim and Alan Willsky

Elements of Information Theory by Thomas M. Cover and Joy A. Thomas

Computer Simulation Using Particles by R.W. Hockney and J.W. Eastwood

Topics in Applied Physics: Volume 25 Laser Beam Propagation in the Atmosphere; Edited by: John W. Strohbehn.

Understanding LASER technology: Second Edition by C. Breck Hitz.

Mechanics of Motor Proteins and the Cytoskeleton by Jonathon Howard.

Science & Music by Sir James Jeans.

Innumeracy: Mathematical Illiteracy and Its Consequences by John Allen Paulos.

Radar Principles for the Non-Specialist by J. C. Toomay.

Approximation Theory: From Taylor Polynomials to Wavelets by Ole Christensen and Khadija Laghrida Christensen.

FOURIER ANALYSIS AND GENERALISED FUNCTIONS by M. J. Lighthill F.R.S.

Modeling Differential Equations in Biology by Clifford Henry Taubes.

Introduction to Graph Theory by Richard J. Trudeau.

Generatingfunctionology: Second Edition by Herbert S. Wilf.

Slicing Pizzas, Racing Turtles, and Further Adventures in Applied Mathematics by Robert B. Banks.