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Structure and Interpretation of Computer Programs
Structure and Interpretation of Computer Programs has had a dramatic impact on computer science curricula over the past decade. This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.
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Introduction to HPC with MPI for Data Science
This gentle introduction to High Performance Computing (HPC) for Data Science using the Message Passing Interface (MPI) standard has been designed as a first course for undergraduates on parallel programming on distributed memory models, and requires only basic programming notions.Divided into two parts the first part covers high performance computing using C++ with the Message Passing Interface (MPI) standard followed by a second part providing high-performance data analytics on computer clusters.In the first part, the fundamental notions of blocking versus non-blocking point-to-point communications, global communications (like broadcast or scatter) and collaborative computations (reduce), with Amdalh and Gustafson speed-up laws are described before addressing parallel sorting and parallel linear algebra on computer clusters. The common ring, torus and hypercube topologies of clusters are then explained and global communication procedures on these topologies are studied. This first part closes with the MapReduce (MR) model of computation well-suited to processing big data using the MPI framework.In the second part, the book focuses on high-performance data analytics. Flat and hierarchical clustering algorithms are introduced for data exploration along with how to program these algorithms on computer clusters, followed by machine learning classification, and an introduction to graph analytics. This part closes with a concise introduction to data core-sets that let big data problems be amenable to tiny data problems.Exercises are included at the end of each chapter in order for students to practice the concepts learned, and a final section contains an overall exam which allows them to evaluate how well they have assimilated the material covered in the book.
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Introduction to Programming with C++ for Engineers
A complete textbook and reference for engineers to learn the fundamentals of computer programming with modern C++ Introduction to Programming with C++ for Engineers is an original presentation teaching the fundamentals of computer programming and modern C++ to engineers and engineering students. Professor Cyganek, a highly regarded expert in his field, walks users through basics of data structures and algorithms with the help of a core subset of C++ and the Standard Library, progressing to the object-oriented domain and advanced C++ features, computer arithmetic, memory management and essentials of parallel programming, showing with real world examples how to complete tasks. He also guides users through the software development process, good programming practices, not shunning from explaining low-level features and the programming tools. Being a textbook, with the summarizing tables and diagrams the book becomes a highly useful reference for C++ programmers at all levels. Introduction to Programming with C++ for Engineers teaches how to program by: Guiding users from simple techniques with modern C++ and the Standard Library, to more advanced object-oriented design methods and language featuresProviding meaningful examples that facilitate understanding of the programming techniques and the C++ language constructionsFostering good programming practices which create better professional programmersMinimizing text descriptions, opting instead for comprehensive figures, tables, diagrams, and other explanatory materialGranting access to a complementary website that contains example code and useful links to resources that further improve the reader’s coding abilityIncluding test and exam question for the reader’s review at the end of each chapter Engineering students, students of other sciences who rely on computer programming, and professionals in various fields will find this book invaluable when learning to program with C++.
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Computer-based Problem Solving Process
One side-effect of having made great leaps in computing over the last few decades, is the resulting over-abundance in software tools created to solve the diverse problems. Problem solving with computers has, in consequence, become more demanding; instead of focusing on the problem when conceptualizing strategies to solve them, users are side-tracked by the pursuit of even more programming tools (as available).Computer-Based Problem Solving Process is a work intended to offer a systematic treatment to the theory and practice of designing, implementing, and using software tools during the problem solving process. This method is obtained by enabling computer systems to be more Intuitive with human logic rather than machine logic. Instead of software dedicated to computer experts, the author advocates an approach dedicated to computer users in general. This approach does not require users to have an advanced computer education, though it does advocate a deeper education of the computer user in his or her problem domain logic.This book is intended for system software teachers, designers and implementers of various aspects of system software, as well as readers who have made computers a part of their day-today problem solving.
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Introduction to Numerical Programming
Makes Numerical Programming More Accessible to a Wider AudienceBearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity.Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-HowThe book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning. Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionalityContains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problemsAddresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysisThis text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.
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MATLAB® for Electrical and Computer Engineering Students and Professionals
This book combines the teaching of the MATLAB® programming language with the presentation and development of carefully selected electrical and computer engineering (ECE) fundamentals. This is what distinguishes it from other books concerned with MATLAB®: it is directed specifically to ECE concerns. Students will see, quite explicitly, how and why MATLAB® is well suited to solve practical ECE problems. This book is intended primarily for the freshman or sophomore ECE major who has no programming experience, no background in EE or CE, and is required to learn MATLAB® programming. It can be used for a course about MATLAB® or an introduction to electrical and computer engineering, where learning MATLAB® programming is strongly emphasized. A first course in calculus, usually taken concurrently, is essential. The book will also serve EE or CE professionals who need to learn MATLAB® and who prefer learning via examples directly relevant to their work. The distinguishing feature of this MATLAB® book is that about 15 per cent develops ECE fundamentals gradually, from very basic principles. Because these fundamentals are interwoven throughout, MATLAB® can be applied to solve relevant, practical problems. The plentiful, in-depth example problems to which MATLAB® is applied were carefully chosen so that results obtained with MATLAB® also provide insights about the fundamentals.
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