Logo

Foundations of Computation by Carol Critchlow, David Eck

Small book cover: Foundations of Computation

Foundations of Computation
by

Publisher: Hobart and William Smith Colleges
Number of pages: 256

Description:
The first half of the course covers material on logic, sets, and functions that would often be taught in a course in discrete mathematics. The second part covers material on automata, formal languages, and grammar that would ordinarily be encountered in an upper level course in theoretical computer science.

Home page url

Download or read it online for free here:
Download link
(1.7MB, PDF)

Similar books

Book cover: Computer Science from the Bottom UpComputer Science from the Bottom Up
by - bottomupcs.com
Computer Science from the Bottom Up: a free, online book designed to teach computer science from the bottom end up. Topics covered include binary and binary logic, operating systems internals, toolchain fundamentals and system library fundamentals.
(14425 views)
Book cover: Handbook of Knowledge RepresentationHandbook of Knowledge Representation
by - Elsevier Science
Knowledge Representation is concerned with encoding knowledge on computers to enable systems to reason automatically. The Handbook of Knowledge Representation is an up-to-date review of twenty-five key topics in knowledge representation.
(10721 views)
Book cover: Introduction to High-Performance Scientific ComputingIntroduction to High-Performance Scientific Computing
by - University of Texas
A computational scientist needs knowledge of several aspects of numerical analysis and discrete mathematics. This text covers: computer architecture, parallel computers, machine arithmetic, numerical linear algebra, applications.
(12370 views)
Book cover: Computational and Inferential Thinking: The Foundations of Data ScienceComputational and Inferential Thinking: The Foundations of Data Science
by
Data Science is about drawing useful conclusions from large and diverse data sets through exploration, prediction, and inference. Our primary tools for exploration are visualizations and descriptive statistics, for prediction are machine learning ...
(7333 views)