Books by "David R. Case"
7 books found
Connecting Discrete Mathematics and Computer Science
by David Liben-Nowell
2022 · Cambridge University Press
An approachable textbook connecting the mathematical foundations of computer science to broad-ranging and compelling applications throughout the field.
The Essentials of Marketing Research
by Lawrence Silver, Roberts Stevens, Bruce Wrenn, David Loudon
2021 · SAGE Publications
Identifying and assessing information is a key to a successful marketing strategy. The Essentials of Marketing Research, 4th Edition has been totally revamped and guides the student in designing, conducting and interpreting marketing research. This comprehensive textbook covers the full range of topics including secondary research and data mining, marketing research ethics, internet marketing research, qualitative and exploratory research, data collection tool design and deployment, qualitative data analysis, statistical analysis, and research report preparation.
This long awaited second edition of this bestseller continues toprovide a comprehensive, user friendly, down-to-earth guide toelementary statistics. The book presents a detailed account ofthe most important procedures for the analysis of data, from thecalculation of simple proportions, to a variety of statisticaltests, and the use of regression models for modeling of clinicaloutcomes. The level of mathematics is kept to a minimum to make thematerial easily accessible to the novice, and a multitude ofillustrative cases are included in every chapter, drawn from thecurrent research literature. The new edition has beencompletely revised and updated and includes new chapters on basicquantitative methods, measuring survival, measurement scales,diagnostic testing, bayesian methods, meta-analysis and systematicreviews. "... After years of trying and failing, this is the only book onstatistics that i have managed to read and understand" - NaveedKirmani, Surgical Registrar, South London Healthcare HHS Trust,UK
This volume reviews the subject of Kac-Moody and Virasoro Algebras. It serves as a reference book for physicists with commentary notes and reprints.
You know how to write Python. Now master the computer science that makes it work. If you’ve been programming for a while, you may have found yourself wondering about the deeper principles behind the code. How are programming languages implemented? What does an interpreter really do? How does the microprocessor execute instructions at a fundamental level? How does a machine learning algorithm make decisions? Computer Science from Scratch is for experienced Python programmers who want to fill in those gaps—not through abstract lectures, but through carefully designed projects that bring core CS concepts to life. Understanding these fundamental building blocks will make you a more versatile and effective programmer. Each chapter presents a focused, hands-on project that teaches a fundamental idea in computer science: INTERPRETERS: Understand syntax, parsing, and evaluation by writing a BASIC interpreter EMULATORS: Learn computer architecture by building an NES emulator from the ground up GRAPHICS: Explore image manipulation and algorithmic art through computer graphics projects MACHINE LEARNING: Demystify classification by implementing a simple, readable KNN model These projects aren’t about building tools—they’re structured lessons that use code to reveal how computing works. Each chapter concludes with real-world context, thoughtful extensions, and exercises to deepen your understanding. Authored by David Kopec, a computer science professor and author of the popular Classic Computer Science Problems series, this is not a beginner’s book, and it’s not a theory-heavy academic text. It’s a practical, code-driven introduction to the essential ideas and mechanisms of computer science—written for programmers who want more than syntax. If you’ve been writing Python and are ready to explore the foundations behind computing, this book will guide you there—with clarity, depth, and purpose.
The ancient game of Go is one of the less obvious candidates for mathematical analysis. With the development of new concepts in combinatorial game theory, the authors have been able to analyze Go games and find solutions to real endgame problems that have stumped professional Go players. Go players with an interest in mathematics and mathematicians
Parallel Distributed Processing, Volume 2
by James L. Mcclelland, David E. Rumelhart, PDP Research Group
1987 · MIT Press
What makes people smarter than computers? These volumes by a pioneering neurocomputing group suggest that the answer lies in the massively parallel architecture of the human mind. They describe a new theory of cognition called connectionism that is challenging the idea of symbolic computation that has traditionally been at the center of debate in theoretical discussions about the mind. The authors' theory assumes the mind is composed of a great number of elementary units connected in a neural network. Mental processes are interactions between these units which excite and inhibit each other in parallel rather than sequential operations. In this context, knowledge can no longer be thought of as stored in localized structures; instead, it consists of the connections between pairs of units that are distributed throughout the network. Volume 1 lays the foundations of this exciting theory of parallel distributed processing, while Volume 2 applies it to a number of specific issues in cognitive science and neuroscience, with chapters describing models of aspects of perception, memory, language, and thought.