Advanced penetration testing*: Hacking the world's most secure networks; Allsopp; 2017.
Advanced programming in the UNIX environment; Stevens & Rago; 3rd ed. 2013.
Algorithms; Sedgewick; 4th ed. 2016.
Algorithms illuminated: The basics; Roughgarden: The Basics; 2017.
Algorithms illuminated: Graph algorithms and data structures; Roughgarden; 2017.
Algorithms illuminated : Part 3, greedy algorithms and dynamic programming; Roughgarden; 2017.
Available for the library to purchase by request: Part 4: ALGORITHMS ILLUMINATED: ALGORITHMS FOR NP-HARD PROBLEMS.
Applied predictive modeling; Kuhn & Johnson; 2013.
Bitcoin and cryptocurrency technologies: A comprehensive introduction; Narayanan; 2019.
C programming language, Kernighan; 2nd ed. 1988.
Clean code: A handbook of agile software craftsmanship; Martin; 2009.
Cloud computing for science and engineering; Foster & Gannon; 2017.
Compilers: Principles, techniques, & tools; Aho; 2nd ed. 2007.
Complex networks: A networking and signal processing perspective; Manoj, Chakraborty, & Singh; 2018.
Computer programming with C++; Pimparkhede; 2017.
Concrete mathematics: A foundation for computer science; 2nd ed. 1994.
Cracking the coding interview: 189 programming questions and solutions*; McDowell; 2015.
Data science design manual; Skiena; 2017.
Available for the library to purchase by request: Deep learning; Goodfellow; 2016.
*Deep learning*; Kelleher; 2019.
Available for the library to purchase by request: Deep learning with Python; Chollet; 2nd ed. 2021.
Discrete-time signal processing; Oppenheim et al.; 3rd ed. 2014.
*Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan*; Kruschke; 2nd ed. 2015.
Foundations of machine learning for predictive data analytics*; Kelleher, et al; 2015.
Foundations of modern networking: SDN, NFV, QoE, IoT, and Cloud; Stallings; 2016.
Fundamentals of numerical computation; Druscoll & Braum; 2018.
Game programming patterns; Nystrom; 2014.
Graph data modeling for NoSQL and SQL: Visualize structure and meaning; Frisendal; 2016,
Graphs, algorithms, and optimization; Kocay & Kreher; 2nd ed. 2017.
Hacker's delight; Warren; 2nd ed. 2013.
How to design programs: An introduction to programming and computing; Felleisen et al.; 2nd ed. 2018.
Introduction to cryptography: Principles and applications; Delfs & Knebl; 3rd ed. 2015.
Introduction to data mining; Tan et al.; 2nd ed. 2019.
Introduction to deep learning; Charniak; 2018.
*An introduction to statistical learning: With applications in R*; James, Witten, Hastie, & Tibshirani; 2015. (2 copies)
*MATLAB: A practical introduction to programming and problem solving*; Attaway; 5th ed. 2019.
Matrix computations*; Golub & Van Loan; 4th ed. 2013.
*Network security assessment*; McNab; 3rd ed. 2017.
Neural networks and deep learning: A textbook; Aggarwal; 2018.
*Numerical algorithms: Methods for computer vision, machine learning, and graphics*; Solomon; 2015.
Numerical methods for engineers and scientists: An introduction with applications using MATLAB®; Gilat; 3rd ed. 2014.
Patent it Yourself : Your Step-by-Step Guide to Filing at the U.S. Patent Office; Pressman; 19th ed. 2018.
*Patent searching made easy: How to do patent searches online and in the library*; 7th ed. 2017.
Available for the library to purchase by request: Patent searching made easy : how to do patent searches online and in the library; 8th ed. 2022.
Pragmatic AI: An introduction to cloud based machine learning; Gift; 2019.
Reinforcement learning: An introduction; 2nd ed. 2018
Serious cryptography: A practical introduction to modern encryption*; Aumasson; 2018.
Signal and power integrity -- simplified; Bogatin; 3rd ed. 2018.
Signals and systems using MATLAB; Chaparro & Akan; 3rd ed. 2019.
Software languages: Syntax, semantics, and metaprogramming; Lammel; 2018,
A tour of C++; Stroustrup; 2nd ed. 2018.
A tour through graph theory; Saoub; 2018.
Algebra for applications: Cryptography, secret sharing, error-correcting, fingerprinting, compression; Slinko; 2015.
Convex Optimization; Boyd & Vandenberghe; 2004.
Computer vision: Models, learning, and inference; Prince; 2012.
Decision making under uncertainty: Theory and applications; Kochenderfer; 2015.
Graph algorithms in the language of linear algebra; Kepler & Gilbert; SIAM; 2011.
LaTeX in 24 hours : A practical guide for scientific writing ; Datta; 2017.
Practical LaTeX *; Grätzer; 2014.
Princeton companion to applied mathematics*; 2015.
Probabilistic robotics; Thrun, Burgard, & Fox; 2006.
Seminumerical algorithms; vol. 2 of Art of Programming; Knuth; 3rd ed. 1997.
Signals, systems, and inference; Oppenheim; 2016.