"Discusses the fundamentals of computation and programming in C language"--

The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.

Providing in-depth coverage, this book covers the fundamentals of computation and programming in C language. Essential concepts including operators and expressions, input and output statements, loop statements, arrays, pointers, functions, strings and preprocessors are described in a lucid manner. A unique approach - 'Learn by quiz' - features questions based on confidence-based learning methodology. It helps the reader to identify the right answer with adequate explanation and reasoning as to why the other options are incorrect. Computer programs and review questions are interspersed throughout the text. The book is appropriate for undergraduate students of engineering, computer science and information technology. It can be used for self-study and assists in the understanding of theoretical concepts and their applications.

This text teaches the essentials of C programming, concentrating on what readers need to know in order to produce stand-alone programs and so solve typical scientific and engineering problems. It is a learning-by-doing book, with many examples and exercises, and lays a foundation of scientific programming concepts and techniques that will prove valuable for those who might eventually move on to another language. Written for undergraduates who are familiar with computers and typical applications but are new to programming.

This book teaches computer programming to the complete beginner using the native C language. As such, it assumes you have no knowledge whatsoever about programming. The main goal of this book is to teach fundamental programming principles using C, one of the most widely used programming languages in the world today. We discuss only those features and statements in C that are necessary to achieve our goal. Once you learn the principles well, they can be applied to any language. If you are worried that you are not good at high-school mathematics, don’t be. It is a myth that you must be good at mathematics to learn programming. C is considered a ‘modern’ language even though its roots date back to the 1970s. Originally, C was designed for writing ‘systems’ programs—things like operating systems, editors, compilers, assemblers and input/output utility programs. But, today, C is used for writing all kinds of applications programs as well—word processing programs, spreadsheet programs, database management programs, accounting programs, games, robots, embedded systems/electronics (i.e., Arduino), educational software—the list is endless. Note: Appendices A-D are available as part of the free source code download at the Apress website. What You Will Learn: How to get started with programming using the C language How to use the basics of C How to program with sequence, selection and repetition logic How to work with characters How to work with functions How to use arrays Who This Book Is For: This book is intended for anyone who is learning programming for the first time.

Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Contents Tutorial • Applications • Further Reading

The authors provide clear examples and thorough explanations of every feature in the C language. They teach C vis-a-vis the UNIX operating system. A reference and tutorial to the C programming language. Annotation copyrighted by Book News, Inc., Portland, OR

The important aspect of designing and and writing this book of c language is to create a foundation for any beginner who wants to learns the c language. The book is designed in such a way that all topics can be easily understood by any novice as well as we have provided variety of c programs to study and to practice.

A variety of programming models relevant to scientists explained, with an emphasis on how programming constructs map to parts of the computer. What makes computer programs fast or slow? To answer this question, we have to get behind the abstractions of programming languages and look at how a computer really works. This book examines and explains a variety of scientific programming models (programming models relevant to scientists) with an emphasis on how programming constructs map to different parts of the computer's architecture. Two themes emerge: program speed and program modularity. Throughout this book, the premise is to "get under the hood," and the discussion is tied to specific programs. The book digs into linkers, compilers, operating systems, and computer architecture to understand how the different parts of the computer interact with programs. It begins with a review of C/C++ and explanations of how libraries, linkers, and Makefiles work. Programming models covered include Pthreads, OpenMP, MPI, TCP/IP, and CUDA.The emphasis on how computers work leads the reader into computer architecture and occasionally into the operating system kernel. The operating system studied is Linux, the preferred platform for scientific computing. Linux is also open source, which allows users to peer into its inner workings. A brief appendix provides a useful table of machines used to time programs. The book's website (https://github.com/divakarvi/bk-spca) has all the programs described in the book as well as a link to the html text.