**Efrem G. Mallach**

February 17, 2020

Most information systems textbooks overwhelm business students with overly technical information they may not need in their careers. This textbook takes a new approach to the required information systems course for business majors. For each topic covered, the text highlights key "Take-Aways" that...

**Bernd S. Palm**

February 06, 2020

Master the complexities of the world's bestselling 2D and 3D software with Introduction to AutoCAD 2020. Ideally suited to new users, and relevant for both AutoCAD 2020 and AutoCAD 2021, this book will be a useful resource for drawing modules in both vocational and introductory undergraduate...

**Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam**

January 14, 2020

This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and...

**Silvelyn Zwanzig, Behrang Mahjani**

December 02, 2019

This textbook gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, SIMEX, variable selection, density...

**Dirk P. Kroese, Zdravko Botev, Thomas Taimre, Radislav Vaisman**

November 22, 2019

"This textbook is a well-rounded, rigorous, and informative work presenting the mathematics behind modern machine learning techniques. It hits all the right notes: the choice of topics is up-to-date and perfect for a course on data science for mathematics students at the advanced undergraduate or...

**Rafael A. Irizarry**

November 08, 2019

Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop...

**Jichun Li, Yi-Tung Chen**

October 11, 2019

In this popular text for an Numerical Analysis course, the authors introduce several major methods of solving various partial differential equations (PDEs) including elliptic, parabolic, and hyperbolic equations. It covers traditional techniques including the classic finite difference method,...

**A.C. Faul**

August 12, 2019

The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms are often taught side by side without showing the similarities and differences between them. This book addresses the...

**Uri Alon**

August 01, 2019

Praise for the first edition: … superb, beautifully written and organized work that takes an engineering approach to systems biology. Alon provides nicely written appendices to explain the basic mathematical and biological concepts clearly and succinctly without interfering with the main text. He...

**Jiacun Wang, William Tepfenhart**

July 03, 2019

Formal Methods in Computer Science gives students a comprehensive introduction to formal methods and their application in software and hardware specification and verification. The first part introduces some fundamentals in formal methods, including set theory, functions, finite state machines,...

**Katherine A. Hughes**

June 21, 2019

Graphic Design: Learn It, Do It is an introduction to the fundamentals of graphic design and the Adobe Creative Cloud applications used to put these concepts into practice. This book is intended for production-oriented audiences, those interested in the what, why and how of graphic design. The "...

**Norman Matloff**

June 20, 2019

Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes...