Start Writing Production-Ready Go Code Fast Thousands of developers and teams want to start taking advantage of Go, the powerful language used in projects ranging from Kubernetes to Docker and Vault. Go Fundamentals is specifically designed to get you up-to-speed fast, to leverage your existing knowledge of other languages, and to help you avoid common mistakes made by Go newcomers. Based on author Mark Bates's and Cory LaNou's pioneering Gopher Guides training curricula, this guide will allow you to quickly understand and use Go syntax, core features, and idioms. Reflecting Go through version 1.18--which includes Go's exciting new support for generics--this guide prepares you to write robust, reliable, well-performing production code right from the outset. Learn how Go manages packages, modules, and dependencies Apply Go basics, such as variable declaration, types, and control flow Work effectively with collection types, iteration, functions, structs, and pointers Understand Go Slices and use them properly Write idiomatic Go, using principles such as embedding and composition Expertly use concurrency to improve code performance Create proper tests to quickly identify and fix problems Write simpler, better code with generics and interfaces Take advantage of channels, context, sync primatives, and other advanced features Go is lightweight, simple, and perfect for modern cloud-native and microservices development, which is why Go developers are in such high demand. With this guide and six months' experience with any modern programming language, you'll have what you need to leap into Go programming. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

"R and Data Mining "introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.

Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.

With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, "R and Data Mining" is a valuable, practical guide to a powerful method of analysis.
Presents an introduction into using R for data mining applications, covering most popular data mining techniquesProvides code examples and data so that readers can easily learn the techniquesFeatures case studies in real-world applicationsto help readers apply the techniques in their work"

Discusses core concepts and principles of deep learning in gaming and animation with applications. Covers application of neural networks for intelligent video game character. Discusses automated video generation and real time animation. Covers technological advancements in virtual reality (VR), and augmented reality (AR).

1) The book provides a basic understanding to readers who want to start their career in web application development. The book develops an understanding of the basics concepts and then takes a broader turn to enlighten the readers about the horizons which can be accessed using JavaScript. 2) JavaScript is exhaustively used in almost all kinds of application development, be it the web applications, cross platform mobile applications, server backend applications. JavaScript is now being used for full stack development and is thus used to write independent applications. Since the need for JavaScript web developers is high, the numbers of students should be high as well. 3) As compared to other books in the market, the proposed book would cover more topics (or, better, levels) in a single volume.

This book covers theoretical aspects of the physical processes, derivation of the governing equations and their solutions. It focusses on hydraulics, hydrology, and contaminant transport, including implementation of computer codes with practical examples. Python-based computer codes for all the solution approaches are provided for better understanding and easy implementation. The mathematical models are demonstrated through applications and the results are analyzed through data tables, plots, and comparison with analytical and experimental data. The concepts are used to solve practical applications like surface and ground water flow, flood routing, crop water requirement and irrigation scheduling. Combines the area of computational hydraulics, hydrology, and water resources engineering with Python Gives deep description of the basic equations and the numerical solutions of both 1D and 2D problems including the numerical codes Includes step-by-step translation of numerical algorithms in computer codes with focus on learners and practitioners Demonstration of theory, mathematical models through practical applications Analysis of each example through data tables, plots, and correlation with reality This book is aimed at senior undergraduates and graduate students in Civil Engineering, Coastal Engineering, Hydrology, and Water Resources Engineering.

In any serious engineering discipline, it would be unthinkable to construct a large system without having a precise notion of what is to be built and without verifying how the system is expected to function. Software engineering is no different in this respect.

Formal methods involve the use of mathematical notation and calculus in software development; such methods are difficult to apply to large-scale systems with practical constraints (e.g., limited developer skills, time and budget restrictions, changing requirements). Here Liu claims that formal engineering methods may bridge this gap. He advocates the incorporation of mathematical notation into the software engineering process, thus substantially improving the rigor, comprehensibility and effectiveness of the methods commonly used in industry.

This book provides an introduction to the SOFL (Structured Object-Oriented Formal Language) method that was designed and industry-tested by the author. Written in a style suitable for lecture courses or for use by professionals, there are numerous exercises and a significant real-world case study, so the readers are provided with all the knowledge and examples needed to successfully apply the method in their own projects.

Resolves linear and non-linear data structures in C language using the algorithm, diagrammatically and its time and space complexity analysis. Covers interview questions and MCQs on all topics of campus readiness Identifies possible solutions to each problem. Includes real life and computational applications of linear and non-linear data structures

Explaining cryptography and its mathematical issues in terms specifically designed to reach computer programmers, this book covers all that is needed to write professional level cryptographic code. An expanded and improved version of the very well received first edition, it includes approximately 100 pages of new material as well as numerous improvements in the original text. The CD-ROM features tools and programs for use with the text.

Newly updated with over 150 pages of material on the latest Tcl extensions, "Tcl/Tk: A Developer s Gu"ide is a unique practical tutorial for professional programmers and beginners alike. Starting with a clear picture of the basics, Tcl/Tk covers the variety of tools in this "Swiss army knife" of programming languages, giving you the ability to enhance your programs, extend your application's capabilities, and become a more effective programmer.

This updated edition covers all of the new features of version 8.6, including object-oriented programming and the creation of megawidgets, existing data structure implementations, themed widgets and virtual events. Extensive code snippets and online tutorials in various languages will give you a firm grasp on how to use the Tcl/Tk libraries and interpreters and, most importantly, on what constitutes an effective strategy for using Tcl/Tk.
Includes the latest features of Tcl/Tk 8.6Covers Tcl development tools, popular extensions, and packages to allow developers to solve real-world problems with Tcl/Tk immediatelyProvides straightforward explanations for beginners and offers tips, style guidelines, and debugging techniques for advanced usersCompanion website includes Tcl/Tk tutorials, applications, distributions, and more tools"

It's axiomatic to state that people fear what they do not understand, and this is especially true when it comes to technology. However, despite their prevalence, computers remain shrouded in mystery, and many users feel apprehensive when interacting with them. Smartphones have only exacerbated the issue. Indeed, most users of these devices leverage only a small fraction of the power they hold in their hands. How Things Work: The Computer Science Edition is a roadmap for readers who want to overcome their technophobia and harness the full power of everyday technology. Beginning with the basics, the book demystifies the mysterious world of computer science, explains its fundamental concepts in simple terms, and answers the questions many users feel too intimidated to ask. By the end of the book, readers will understand how computers and smart devices function and, more important, how they can make these devices work for them. To complete the picture, the book also introduces readers to the darker side of modern technology: security and privacy concerns, identity theft, and threats from the Dark Web.

Every programmer and software project manager must master the art of creating reusable software modules; they are the building blocks of large, reliable applications. Unlike some modern object-oriented languages, C provides little linguistic support or motivation for creating reusable application programming interfaces (APIs). While most C programmers use APIs and the libraries that implement them in almost every application they write, relatively few programmers create and disseminate new, widely applicable APIs. C Interfaces and Implementations shows how to create reusable APIs using interface-based design, a language-independent methodology that separates interfaces from their implementations. This methodology is explained by example. The author describes in detail 24 interfaces and their implementations, providing the reader with a thorough understanding of this design approach.

Features of C Interfaces and Implementations:

• Concise interface descriptions that comprise a reference manual for programmers interested in using the interfaces.
• A guided tour of the code that implements each chapter's interface tp help those modifying or extending an interface or designing related interfaces.
• In-depth focus on "algorithm engineering: " how to package data structures and related algorithms into reusable modules.
• Source code for 24 APIs and 8 sample applications is examined, with each presented as a "literate program" in which a thorough explanation is interleaved with the source code.
• Rarely documented C programming tricks-of-the-trade.
• Convenient access to all source code in the book via the World Wide Web at http: //www.cs.princeton.edu/software/cii/

Quickly learn the ropes with the Rust programming language using this practical, step-by-step guide In Beginning Rust Programming, accomplished programmer and author Ric Messier delivers a highly practical, real-world guide to coding with Rust. Avoiding dry, theoretical content and "Hello, world"-type tutorials of questionable utility, the book dives immediately into functional Rust programming that takes advantage of the language's blazing speed and memory efficiency. Designed from the ground up to give you a running start to using the multiparadigm system programming language, this book will teach you to: Solve real-world computer science problems of practical importance Use Rust's rich type system and ownership model to guarantee memory-safety and thread-safety Integrate Rust with other programming languages and use it for embedded devices Perfect for programmers with some experience in other languages, like C or C++, Beginning Rust Programming is also a great pick for students new to programming and seeking a user-friendly and robust language with which to start their coding career.

All traditional implementation techniques for functional languages fail to avoid useless repetition of work. They are not "optimal" in their implementation of sharing, often causing a catastrophic, exponential explosion in reduction time. Optimal reduction is an innovative graph reduction technique for functional expressions, introduced by Lamping in 1990, that solves the sharing problem. This work, the first on the subject, is a comprehensive account by two of its leading exponents. Practical implementation aspects are fully covered as are the mathematical underpinnings of the subject. The relationship to the pioneering work of Lévy and to Girard's more recent "Geometry of Interaction" are explored; optimal reduction is thereby revealed as a prime example of how a beautiful mathematical theory can lead to practical benefit. The book is essentially self-contained, requiring no more than basic familiarity with functional languages. It will be welcomed by graduate students and research workers in lambda calculus, functional programming or linear logic.

Software development has been a troubling since it first started. There are seven chronic problems that have plagued it from the beginning: Incomplete and ambiguous user requirements that grow by >2% per month. Major cost and schedule overruns for large applications > 35% higher than planned. Low defect removal efficiency (DRE) < 85% on large systems. Cancelled projects that are not completed: > 30% above 10,000 function points. Poor quality and low reliability after the software is delivered: > 5 bugs per FP. Breach of contract litigation against software outsource vendors. Expensive maintenance and enhancement costs after delivery. These are endemic problems for software executives, software engineers and software customers but they are not insurmountable. In Software Development Patterns and Antipatterns, software engineering and metrics pioneer Capers Jones presents technical solutions for all seven. The solutions involve moving from harmful patterns of software development to effective patterns of software development. The first section of the book examines common software development problems that have been observed in many companies and government agencies. The data on the problems comes from consulting studies, breach of contract lawsuits, and the literature on major software failures. This section considers the factors involved with cost overruns, schedule delays, canceled projects, poor quality, and expensive maintenance after deployment. The second section shows patterns that lead to software success. The data comes from actual companies. The section's first chapter on Corporate Software Risk Reduction in a Fortune 500 company was based on a major telecom company whose CEO was troubled by repeated software failures. The other chapters in this section deal with methods of achieving excellence, as well as measures that can prove excellence to C-level executives, and with continuing excellence through the maintenance cycle as well as for software development.

Software development has been a troubling since it first started. There are seven chronic problems that have plagued it from the beginning: Incomplete and ambiguous user requirements that grow by >2% per month. Major cost and schedule overruns for large applications > 35% higher than planned. Low defect removal efficiency (DRE) < 85% on large systems. Cancelled projects that are not completed: > 30% above 10,000 function points. Poor quality and low reliability after the software is delivered: > 5 bugs per FP. Breach of contract litigation against software outsource vendors. Expensive maintenance and enhancement costs after delivery. These are endemic problems for software executives, software engineers and software customers but they are not insurmountable. In Software Development Patterns and Antipatterns, software engineering and metrics pioneer Capers Jones presents technical solutions for all seven. The solutions involve moving from harmful patterns of software development to effective patterns of software development. The first section of the book examines common software development problems that have been observed in many companies and government agencies. The data on the problems comes from consulting studies, breach of contract lawsuits, and the literature on major software failures. This section considers the factors involved with cost overruns, schedule delays, canceled projects, poor quality, and expensive maintenance after deployment. The second section shows patterns that lead to software success. The data comes from actual companies. The section's first chapter on Corporate Software Risk Reduction in a Fortune 500 company was based on a major telecom company whose CEO was troubled by repeated software failures. The other chapters in this section deal with methods of achieving excellence, as well as measures that can prove excellence to C-level executives, and with continuing excellence through the maintenance cycle as well as for software development.

Fundamentals of Engineering Programming with C and Fortran, first published in 1998, is a beginner's guide to problem solving with computers which shows how to quickly prototype a program for a particular engineering application. The book's side by side coverage of C and Fortran, the predominant computer languages in engineering, is unique. It emphasizes the importance of developing programming skills in C while carefully presenting the importance of maintaining a good reading knowledge of Fortran. Beginning with a brief description of computer architecture, the book then covers the fundamentals of computer programming for problem solving. It devotes separate chapters to data types and operators, control flow, type conversion, arrays, and file operations. The final chapter contains case studies that illustrate particular elements of modeling and visualization. Also included are a number of appendices covering C and Fortran language summaries and other useful topics. This concise and accessible book can be used as a text for introductory-level undergraduate courses on engineering programming or as a self-study guide for practising engineers.

Based on the practical experiences of its authors, who collectively have spent several decades teaching software skills to scientists. Readers only need a basic understanding of Python includes over a hundred exercises to allow readers to practice their skills

A unique approach to "Intro CS." In a nutshell, the authors of this book's objective is to provide an introduction to computer science as an intellectually rich and vibrant field rather than focusing exclusively on computer programming. While programming is certainly an important and pervasive element of their approach, they emphasize concepts and problem-solving over syntax and programming language features. This book is a companion to the course "CS for All" developed at Harvey Mudd College and subsequently adopted at a variety of colleges and universities. At Mudd, this course is taken by almost every first-year student - irrespective of the student's ultimate major - as part of the college's core curriculum. The offering is also taken by many students at the Claremont Colleges, including students majoring in the humanities, social sciences, and the arts. Thus, it serves as a first computing course for students regardless of their major. This book is intended to be used with the substantial resources that we have developed for the course. These resources include complete lecture slides, a rich collection of weekly assignments, some accompanying software, documentation, and papers that have been published about the course. The authors have deliberately kept this book relatively short and have endeavored to make it fun and readable. The content of this book is an accurate reflection of the content of the course rather than an intimidating encyclopedic tome that can't possibly be covered in a single semester. The book has been written in the belief that a student can read all of it comfortably as the course proceeds.

A valuable learning tool for students and an indispensable resource for professional scientists and engineers

Several outstanding features make this book a superior introduction to modern statistical mechanics: It is the only intermediate-level text offering comprehensive coverage of both basic statistical mechanics and modern topics such as molecular dynamic methods, renormalization theory, chaos, polymer chain folding, oscillating chemical reactions, and cellular automata. It is also the only text written at this level to address both equilibrium and nonequilibrium statistical mechanics. Finally, students and professionals alike will appreciate such aids to comprehension as detailed derivations for most equations, more than 100 chapter-end exercises, and 15 computer programs written in FORTRAN that illustrate many of the concepts covered in the text.

Statistical Mechanics begins with a refresher course in the essentials of modern statistical mechanics which, on its own, can serve as a handy pocket guide to basic definitions and formulas. Part II is devoted to equilibrium statistical mechanics. Readers will find in-depth coverage of phase transitions, critical phenomena, liquids, molecular dynamics, Monte Carlo techniques, polymers, and more. Part III focuses on nonequilibrium statistical mechanics and progresses in a logical manner from near-equilibrium systems, for which linear responses can be used, to far-from-equilibrium systems requiring nonlinear differential equations.

Software Engineering: A Methodical Approach (Second Edition) provides a comprehensive, but concise introduction to software engineering. It adopts a methodical approach to solving software engineering problems, proven over several years of teaching, with outstanding results. The book covers concepts, principles, design, construction, implementation, and management issues of software engineering. Each chapter is organized systematically into brief, reader-friendly sections, with itemization of the important points to be remembered. Diagrams and illustrations also sum up the salient points to enhance learning. Additionally, the book includes the author's original methodologies that add clarity and creativity to the software engineering experience. New in the Second Edition are chapters on software engineering projects, management support systems, software engineering frameworks and patterns as a significant building block for the design and construction of contemporary software systems, and emerging software engineering frontiers. The text starts with an introduction of software engineering and the role of the software engineer. The following chapters examine in-depth software analysis, design, development, implementation, and management. Covering object-oriented methodologies and the principles of object-oriented information engineering, the book reinforces an object-oriented approach to the early phases of the software development life cycle. It covers various diagramming techniques and emphasizes object classification and object behavior. The text features comprehensive treatments of: Project management aids that are commonly used in software engineering An overview of the software design phase, including a discussion of the software design process, design strategies, architectural design, interface design, database design, and design and development standards User interface design Operations design Design considerations including system catalog, product documentation, user message management, design for real-time software, design for reuse, system security, and the agile effect Human resource management from a software engineering perspective Software economics Software implementation issues that range from operating environments to the marketing of software Software maintenance, legacy systems, and re-engineering This textbook can be used as a one-semester or two-semester course in software engineering, augmented with an appropriate CASE or RAD tool. It emphasizes a practical, methodical approach to software engineering, avoiding an overkill of theoretical calculations where possible. The primary objective is to help students gain a solid grasp of the activities in the software development life cycle to be confident about taking on new software engineering projects.

Based on the practical experiences of its authors, who collectively have spent several decades teaching software skills to scientists. Readers only need a basic understanding of Python includes over a hundred exercises to allow readers to practice their skills

Developing Graphics Frameworks with Python and OpenGL shows you how to create software for rendering complete three-dimensional scenes. The authors explain the foundational theoretical concepts as well as the practical programming techniques that will enable you to create your own animated and interactive computer-generated worlds. You will learn how to combine the power of OpenGL, the most widely adopted cross-platform API for GPU programming, with the accessibility and versatility of the Python programming language. Topics you will explore include generating geometric shapes, transforming objects with matrices, applying image-based textures to surfaces, and lighting your scene. Advanced sections explain how to implement procedurally generated textures, postprocessing effects, and shadow mapping. In addition to the sophisticated graphics framework you will develop throughout this book, with the foundational knowledge you will gain, you will be able to adapt and extend the framework to achieve even more spectacular graphical results.

Microservices architecture (MSA) is increasingly popular with software architects and engineers as it accelerates software solution design, development, and deployment in a risk-free manner. Placing a software system into a production environment is elegantly simplified and sped up with the use of MSA development platforms, runtime environments, acceleration engines, design patterns, integrated frameworks, and related tools. The MSA ecosystem is expanding with third-party products that automate as many tasks as possible. MSA is being positioned as the enterprise-grade and agile-application design method. This book covers in-depth the features and facilities that make up the MSA ecosystem. Beginning with an overview of Service-Oriented Architecture (SOA) that covers the Common Object Request Broker Architecture (CORBA), Distributed Component Object Model (DCOM), and Remote Method Invocation (RMI), the book explains the basic essentials of MSA and the continuous delivery of applications to customers. The book gives software developers insight into: Current and emerging communication models Key architectural elements of MSA-based applications Designing efficient APIs for microservices MSA middleware platforms such as REST, SOAP, Apache Thrift, and gRPC Microservice discovery and the API gateway Service orchestration and choreography for composing individual services to achieve a useful business process Database transactions in MSA-centric applications Design, composition, security, and deployment patterns MSA security Modernizing legacy applications The book concludes with a chapter on composing and building powerful microservices. With the exponential growth of IoT devices, microservices are being developed and deployed on resource-constrained but resource-intensive devices in order to provide people-centric applications. The book discusses the challenges of these applications. Finally, the book looks at the role of microservices in smart environments and upcoming trends including ubiquitous yet disappearing microservices.

This book meant for those who seek to apply evolutionary algorithms to problems in engineering and science. To this end, it provides the theoretical background necessary to the understanding of the presented evolutionary algorithms and their shortcomings, while also discussing themes that are pivotal to the successful application of evolutionary algorithms to real-world problems. The theoretical descriptions are illustrated with didactical Python implementations of the algorithms, which not only allow readers to consolidate their understanding, but also provide a sound starting point for those intending to apply evolutionary algorithms to optimization problems in their working fields. Python has been chosen due to its widespread adoption in the Artificial Intelligence community. Those familiar with high level languages such as MATLAB (TM) will not have any difficulty in reading the Python implementations of the evolutionary algorithms provided in the book. Instead of attempting to encompass most of the existing evolutionary algorithms, past and present, the book focuses on those algorithms that researchers have recently applied to difficult optimization problems, such as control problems with continuous action spaces and the training of high-dimensional convolutional neural-networks. The basic characteristics of real-world optimization problems are presented, together with recommendations on its proper application to evolutionary algorithms. The applied nature of the book is reinforced by the presentation of successful cases of the application of evolutionary algorithms to optimization problems. This is complemented by Python source codes, giving users an insight into the idiosyncrasies of the practical application of evolutionary algorithms.

Recent progress in artificial intelligence (AI) has revolutionized our everyday life. Many AI algorithms have reached human-level performance and AI agents are replacing humans in most professions. It is predicted that this trend will continue and 30% of work activities in 60% of current occupations will be automated. This success, however, is conditioned on availability of huge annotated datasets to training AI models. Data annotation is a time-consuming and expensive task which still is being performed by human workers. Learning efficiently from less data is a next step for making AI more similar to natural intelligence. Transfer learning has been suggested a remedy to relax the need for data annotation. The core idea in transfer learning is to transfer knowledge across similar tasks and use similarities and previously learned knowledge to learn more efficiently. In this book, we provide a brief background on transfer learning and then focus on the idea of transferring knowledge through intermediate embedding spaces. The idea is to couple and relate different learning through embedding spaces that encode task-level relations and similarities. We cover various machine learning scenarios and demonstrate that this idea can be used to overcome challenges of zero-shot learning, few-shot learning, domain adaptation, continual learning, lifelong learning, and collaborative learning.