With this guide, pioneering Go programmer Mark Summerfield shows how to write code that takes full advantage of Go's breakthrough features and idioms. Both a tutorial and a language reference, "Programming in Go" brings together all the knowledge you need to evaluate Go, think in Go, and write high-performance software with Go. Summerfield presents multiple idiom comparisons showing exactly how Go improves upon older languages, calling special attention to Go's key innovations. Along the way, he explains everything from the absolute basics through Go's lock-free channel-based concurrency and its flexible and unusual duck-typing type-safe approach to object-orientation. Throughout, Summerfield's approach is thoroughly practical. Each chapter offers multiple live code examples designed to encourage experimentation and help you quickly develop mastery. Wherever possible, complete programs and packages are presented to provide realistic use cases, as well as exercises. Coverage includes:-- Quickly getting and installing Go, and building and running Go programs -- Exploring Go's syntax, features, and extensive standard library -- Programming Boolean values, expressions, and numeric types -- Creating, comparing, indexing, slicing, and formatting strings -- Understanding Go's highly efficient built-in collection types: slices and maps -- Using Go as a procedural programming language -- Discovering Go's unusual and flexible approach to object orientation -- Mastering Go's unique, simple, and natural approach to fine-grained concurrency -- Reading and writing binary, text, JSON, and XML files -- Importing and using standard library packages, custom packages, and third-party packages -- Creating, documenting, unit testing, and benchmarking custom packages

    It takes a fairly traditional approach, emphasizing problem solving, design, and programming as the core skills of computer science. However, these ideas are illustrated using a non-traditional language, namely Python. Although I use Python as the language, teaching Python is not the main point of this book. Rather, Python is used to illustrate fundamental principles of design and programming that apply in any language or computing environment. In some places, I have purposely avoided certain Python features and idioms that are not generally found in other languages. There are already many good books about Python on the market; this book is intended as an introduction to computing. Features include the following: *Extensive use of computer graphics. *Interesting examples. *Readable prose. *Flexible spiral coverage. *Just-in-time object coverage. *Extensive end-of-chapter problems.

    This text provides a basic treatment of discrete-event simulation, including the proper collection and analysis of data, the use of analytic techniques, verification and validation of models, and designing simulation experiments. It offers an up-to-date treatment of simulation of manufacturing and material handling systems, computer systems, and computer networks. Students and instructors will find a variety of resources at the associated website, www.bcnn.net, including simulation source code for download, additional exercises and solutions, web links and errata.

    Blends academic precision and practical experience in an authoritative introduction to basic principles of digital design and practical requirements. With over 30 years of experience in both industrial and university settings, the author covers the most widespread logic design practices while building a solid foundation of theoretical and engineering principles for students to use as they go forward in this fast moving field.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    This book provides a clear and comprehensive introduction to the application of electronic control systems in mechanical and electrical engineering. It gives a framework of knowledge that allows engineers and technicians to develop an interdisciplinary understanding and integrated approach to engineering.

    

    Well-known scholars in the field explore the important qualities and functions of English studies' constituent disciplines--Ellen Barton on linguistics and discourse analysis, Janice Lauer on rhetoric and composition, Katharine Haake on creative writing, Richard Taylor on literature and literary criticism, Amy Elias on critical theory and cultural studies, and Robert Yagelski on English education--and the productive differences and similarities among them that define English studies' continuing importance.Faculty and students in both undergraduate and graduate courses will find the volume an invaluable overview of an increasingly fragmented field, as will department administrators who are responsible for evaluating the contributions of diverse faculty members but whose academic training may be specific to one discipline.Each chapter of English Studies is an argument for the value--the right to equal status--of each individual discipline among all English studies disciplines, yet the book is also an argument for disciplinary integration.

    The best description of the first edition comes from two Amazon reviewers; the first proclaiming, "I got the same feeling of enlightenment when reading this one as I did all those years ago when I read the classic book "Code Complete" and the second stating "This is the first game book I have read that I was sorry when I got to the end because there wasn't any more."For Game Coding Complete, Second Edition, McShaffry returns with many more of his highly popular, shoot-from the hips war stories and expert game programming insight that only a real insider could provide. McShaffry uses his experience as a leading programmer for Origin Systems, Microsoft, and Ion Storm a division of Eidos, to illustrate real-world techniques and solutions, including examples from his recent work on the major game, Thief Deadly Shadows. Game Coding Complete, Second Edition takes programmers through the complete process of developing a professional quality game using hundreds of insider tricks and techniques developed and perfect by the author from over a decade of game development experience. It covers a range of topics that will appeal to the most discriminating programmers such as key "gotcha" issues that could trip up even veteran programmers. The new edition features expanded coverage of 3D programming, several new chapters on game interface design, game audio, game scripting, game engine technology, code optimization, production and scheduling, plus it now includes a CD-ROM packed with valuable source code and game development tools. The appendix offers solid advice on starting your own game company. The C++ language is used to explain specific programming concepts with added discussion of development with C# and Managed DirectX programming.

    The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks.The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.

    You'll quickly learn the language's fundamentals, then move onto persistence, exception handling, web development, SQLite, data wrangling, and Google App Engine. You'll also learn how to write mobile apps for Android, all thanks to the power that Python gives you.We think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Python uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    Kai-Fu Lee—one of the world’s most respected experts on AI and China—reveals that China has suddenly caught up to the US at an astonishingly rapid and unexpected pace.In AI Superpowers, Kai-Fu Lee argues powerfully that because of these unprecedented developments in AI, dramatic changes will be happening much sooner than many of us expected. Indeed, as the US-Sino AI competition begins to heat up, Lee urges the US and China to both accept and to embrace the great responsibilities that come with significant technological power.Most experts already say that AI will have a devastating impact on blue-collar jobs. But Lee predicts that Chinese and American AI will have a strong impact on white-collar jobs as well. Is universal basic income the solution? In Lee’s opinion, probably not.  But he provides a clear description of which jobs will be affected and how soon, which jobs can be enhanced with AI, and most importantly, how we can provide solutions to some of the most profound changes in human history that are coming soon.