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Books > Computing & IT > Computer programming > Programming languages
Shading, as part of the creation of realistic computer-generated images, is currently bringing major advances to computer graphics, with important practical applications in computer game design and animation. Shaders are a more sophisticated way of making 3D objects look more realistic. While most shaders are created using proprietary shading languages, Sh, a new open-source system, simplifies the shader programming process by making it part of the C++ language. This book introduces Sh and describes how to program a GPU using C++ to implement both basic and advanced shading techniques. Readers of this book will be able to start writing advanced, modular shaders using Sh within a day
Turn futuristic ideas about computer vision and machine learning into demonstrations that are both functional and entertaining Key Features Build OpenCV 4 apps with Python 2 and 3 on desktops and Raspberry Pi, Java on Android, and C# in Unity Detect, classify, recognize, and measure real-world objects in real-time Work with images from diverse sources, including the web, research datasets, and various cameras Book DescriptionOpenCV 4 is a collection of image processing functions and computer vision algorithms. It is open source, supports many programming languages and platforms, and is fast enough for many real-time applications. With this handy library, you'll be able to build a variety of impressive gadgets. OpenCV 4 for Secret Agents features a broad selection of projects based on computer vision, machine learning, and several application frameworks. To enable you to build apps for diverse desktop systems and Raspberry Pi, the book supports multiple Python versions, from 2.7 to 3.7. For Android app development, the book also supports Java in Android Studio, and C# in the Unity game engine. Taking inspiration from the world of James Bond, this book will add a touch of adventure and computer vision to your daily routine. You'll be able to protect your home and car with intelligent camera systems that analyze obstacles, people, and even cats. In addition to this, you'll also learn how to train a search engine to praise or criticize the images that it finds, and build a mobile app that speaks to you and responds to your body language. By the end of this book, you will be equipped with the knowledge you need to advance your skills as an app developer and a computer vision specialist. What you will learn Detect motion and recognize gestures to control a smartphone game Detect car headlights and estimate their distance Detect and recognize human and cat faces to trigger an alarm Amplify motion in a real-time video to show heartbeats and breaths Make a physics simulation that detects shapes in a real-world drawing Build OpenCV 4 projects in Python 3 for desktops and Raspberry Pi Develop OpenCV 4 Android applications in Android Studio and Unity Who this book is forIf you are an experienced software developer who is new to computer vision or machine learning, and wants to study these topics through creative projects, then this book is for you. The book will also help existing OpenCV users who want upgrade their projects to OpenCV 4 and new versions of other libraries, languages, tools, and operating systems. General familiarity with object-oriented programming, application development, and usage of operating systems (OS), developer tools, and the command line is required.
For freshman/sophomore-level courses in Assembly Language Programming, Introduction to Computer Organization, and Introduction to Computer Architecture. Students using this text will gain an understanding of how the functional components of modern computers are put together and how a computer works at the machine language level. MIPS architecture embodies the fundamental design principles of all contemporary RISC architectures. By incorporating this text into their courses, instructors will be able to prepare their undergraduate students to go on to upper-division computer organization courses.
Understand how to use Explainable AI (XAI) libraries and build trust in AI and machine learning models. This book utilizes a problem-solution approach to explaining machine learning models and their algorithms. The book starts with model interpretation for supervised learning linear models, which includes feature importance, partial dependency analysis, and influential data point analysis for both classification and regression models. Next, it explains supervised learning using non-linear models and state-of-the-art frameworks such as SHAP values/scores and LIME for local interpretation. Explainability for time series models is covered using LIME and SHAP, as are natural language processing-related tasks such as text classification, and sentiment analysis with ELI5, and ALIBI. The book concludes with complex model classification and regression-like neural networks and deep learning models using the CAPTUM framework that shows feature attribution, neuron attribution, and activation attribution. After reading this book, you will understand AI and machine learning models and be able to put that knowledge into practice to bring more accuracy and transparency to your analyses. What You Will Learn Create code snippets and explain machine learning models using Python Leverage deep learning models using the latest code with agile implementations Build, train, and explain neural network models designed to scale Understand the different variants of neural network models Who This Book Is For AI engineers, data scientists, and software developers interested in XAI
Learn to program with Rust 2021 Edition, in an easy, step-by-step manner on Unix, the Linux shell, macOS, and the Windows command line. As you read this book, you'll build on the knowledge you gained in previous chapters and see what Rust has to offer. Beginning Rust starts with the basics of Rust, including how to name objects, control execution flow, and handle primitive types. You'll see how to do arithmetic, allocate memory, use iterators, and handle input/output. Once you have mastered these core skills, you'll work on handling errors and using the object-oriented features of Rust to build robust Rust applications in no time. Only a basic knowledge of programming in C or C++ and familiarity with a command console are required. After reading this book, you'll be ready to build simple Rust applications. What You Will Learn Get started programming with Rust Understand heterogeneous data structures and data sequences Define functions, generic functions, structs, and more Work with closures, changeable strings, ranges and slices Use traits and learn about lifetimes Who This Book Is For Those who are new to Rust and who have at least some prior experience with programming in general: some C/C++ is recommended particularly.
Bring Elixir into your company, with real-life strategies from the people who built Elixir and use it successfully at scale. See how Ben Marx and Bleacher Report maintain one of the highest-traffic Elixir applications by selling the concept to management and delivering on that promise. Find out how Bruce Tate and icanmakeitbetter hire and train Elixir engineers, and the techniques they've employed to design and ensure code consistency since Elixir's early days. Explore customer challenges in deploying and monitoring distributed applications with Jose Valim and Plataformatec. This book has all the information you need to take your application from concept to production. Adoption is more than programming. Elixir is an exciting new language, but to successfully get your application from start to finish, you're going to need to know more than just the language. The case studies and strategies in this book will get you there. Make a business case and build a team before you finish your first prototype. Once you're in development, form strategies for organizing your code and learning the constraints of the runtime and ecosystem. Convince stakeholders, both business and technical, about the value they can expect. Prepare to make the critical early decisions that will shape your application for years to come. Finally, manage your deployment with all of the knobs and gauges that good DevOps teams demand. Decide between the many options available for deployment, and how to best prepare yourself for the challenges of running a production application. This book picks up where most Elixir books let off. It won't teach you to program Elixir, or any of its tools. Instead, it guides you through the broader landscape and shows you a holistic approach to adopting the language. What You Need: This book works with any version of Elixir.
This in-depth guide covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. In this book, you'll implement numerical algorithms in Kotlin using NM Dev, an object-oriented and high-performance programming library for applied and industrial mathematics. Discover how Kotlin has many advantages over Java in its speed, and in some cases, ease of use. In this book, you'll see how it can help you easily create solutions for your complex engineering and data science problems. After reading this book, you'll come away with the knowledge to create your own numerical models and algorithms using the Kotlin programming language. What You Will Learn Program in Kotlin using a high-performance numerical library Learn the mathematics necessary for a wide range of numerical computing algorithms Convert ideas and equations into code Put together algorithms and classes to build your own engineering solutions Build solvers for industrial optimization problems Perform data analysis using basic and advanced statistics Who This Book Is For Programmers, data scientists, and analysts with prior experience programming in any language, especially Kotlin or Java.
This book constitutes the refereed proceedings of the 7th International IFIP WG 2.13 Conference on Open Source Systems, OSS 2010, held in Salvador, Brazil, in October 2011. The 20 revised full papers presented together with 4 industrial full papers and 8 lightning talks were carefully reviewed and selected from 56 submissions. The papers are organized in the following topical sections: OSS quality and reliability, OSS products, review of technologies of and for OSS, knowledge and research building in OSS, OSS reuse, integration, and compliance, OSS value and economics, OSS adoption in industry, and mining OSS repositories.
Ruby, Io, Prolog, Scala, Erlang, Clojure, Haskell. With Seven Languages in Seven Weeks, by Bruce A. Tate, you'll go beyond the syntax-and beyond the 20-minute tutorial you'll find someplace online. This book has an audacious goal: to present a meaningful exploration of seven languages within a single book. Rather than serve as a complete reference or installation guide, Seven Languages hits what's essential and unique about each language. Moreover, this approach will help teach you how to grok new languages. For each language, you'll solve a nontrivial problem, using techniques that show off the language's most important features. As the book proceeds, you'll discover the strengths and weaknesses of the languages, while dissecting the process of learning languages quickly--for example, finding the typing and programming models, decision structures, and how you interact with them. Among this group of seven, you'll explore the most critical programming models of our time. Learn the dynamic typing that makes Ruby, Python, and Perl so flexible and compelling. Understand the underlying prototype system that's at the heart of JavaScript. See how pattern matching in Prolog shaped the development of Scala and Erlang. Discover how pure functional programming in Haskell is different from the Lisp family of languages, including Clojure. Explore the concurrency techniques that are quickly becoming the backbone of a new generation of Internet applications. Find out how to use Erlang's let-it-crash philosophy for building fault-tolerant systems. Understand the actor model that drives concurrency design in Io and Scala. Learn how Clojure uses versioning to solve some of the most difficult concurrency problems. It's all here, all in one place. Use the concepts from one language to find creative solutions in another-or discover a language that may become one of your favorites.
This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you'll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models. Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You'll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you'll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit. After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own. What You Will Learn How to start developing web applications using Streamlit What are Streamlit's components Media elements in Streamlit How to visualize data using various interactive and dynamic Python libraries How to implement models in Streamlit web applications Who This Book Is ForProfessionals working in data science and machine learning domains who want to showcase and deploy their work in a web application with no prior knowledge of web development.
Choose the right programmable logic devices for your projects with this guide to the proprietary details of the alternative architectures and processes of Complex Programmable Logic Devices (CPLD) and Field Programmable Gate Arrays (FPGA). Engineers learn how to select the appropriate development tools and resources and how to optimize and increase the reliability of the design along with the appropriate use of simulation and testing. Engineering managers will gain insight into how to plan, schedule, and budget a CPLD-based or FPGA-based design.
The control-flow issues presented in this textbook are extremely relevant in modern computer languages and programming styles. In addition to the basic control-flow mechanisms, virtually all new computer languages provide some form of exceptional control flow to support robust programming introduced in this textbook. Also, concurrency capabilities are appearing with increasing frequency in both new and old programming languages, and are covered in this book. Understanding Control Flow: With Concurrent Programming Using C++ starts with looping, and works through each of the basic control-flow concepts, examining why each is fundamental and where it is useful. Time is spent on each concept according to its level of difficulty. Examples and exercises are also provided in this textbook. New programming methodologies are requiring new forms of control flow, and new programming languages are supporting these methodologies with new control structures, such as the concurrency constructs discussed in this textbook. Most computers now contain multi-threading and multi-cores, while multiple processors and distributed systems are ubiquitous - all of which require advanced programming methodologies to take full advantage of the available parallelism summarized in this textbook. Advance forms of control flow are becoming basic programming skills needed by all programmers, not just graduate students working in the operating systems or database disciplines. This textbook is designed for advanced-level students studying computer science and engineering. Professionals and researchers working in this field, specifically programming and software engineering, will find this book useful as a reference.
This book provides a comprehensive explanation of precision (i.e., personalized) healthcare and explores how it can be advanced through artificial intelligence (AI) and other data-driven technologies. From improving the diagnosis, treatment, and monitoring of many medical conditions to the effective implementation of precise patient care, this book will help you understand datasets produced from digital health technologies and IoT and teach you how to employ analytical methods such as convolutional neural networks and deep learning to analyze that data. You'll also see how this data-driven approach can enhance and democratize value-based healthcare delivery. Additionally, you'll learn how the convergence of AI and precision health is revolutionizing healthcare, including some of the most difficult challenges facing precision medicine, such as ethics, bias, privacy, and health equity. Precision Health and Artificial Intelligence provides the groundwork for clinicians, engineers, bioinformaticians, and healthcare enthusiasts to apply AI to healthcare. What You Will Learn Understand the components required to facilitate precision health and personalized care Apply and implement precision health systems Overcome the challenges of delivering precision healthcare at scale Reconcile ethical and moral implications of delivering precision healthcare Gain insight into the hurdles providers face while implementing precision healthcare Who This Book Is For Healthcare professionals, clinicians, engineers, bioinformaticians, chief information officers (CIOs), and students
This tutorial offers a full complement of AutoLISP programming skills. Beginning with an introduction to the language, the programming environment, and the Visual LISP editor, succeeding chapters address data manipulation, user input and output options, programming dialog boxes, modifying AutoCAD drawing database objects, and using advanced features of the Visual LISP programming tool kit. Demonstration projects can also serve as core applications for reader's own use.
This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical modeling methods like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive integrated moving-average). Next, you'll learn univariate and multivariate modeling using different open-sourced packages like Fbprohet, stats model, and sklearn. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems. The book concludes by demonstrating the implementation of deep learning models (LSTMs and ANN) for time series forecasting. Each chapter includes several code examples and illustrations. After finishing this book, you will have a foundational understanding of various concepts relating to time series and its implementation in Python. What You Will Learn Implement various techniques in time series analysis using Python. Utilize statistical modeling methods such as AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average) and ARIMA (autoregressive integrated moving-average) for time series forecasting Understand univariate and multivariate modeling for time series forecasting Forecast using machine learning and deep learning techniques such as GBM and LSTM (long short-term memory) Who This Book Is ForData Scientists, Machine Learning Engineers, and software developers interested in time series analysis.
This Brief provides a roadmap for the R language and programming environment with signposts to further resources and documentation.
Haskell is a purely functional language that allows programmers to rapidly develop clear, concise, and correct software. The language has grown in popularity in recent years, both in teaching and in industry. This book is based on the author's experience of teaching Haskell for more than twenty years. All concepts are explained from first principles and no programming experience is required, making this book accessible to a broad spectrum of readers. While Part I focuses on basic concepts, Part II introduces the reader to more advanced topics. This new edition has been extensively updated and expanded to include recent and more advanced features of Haskell, new examples and exercises, selected solutions, and freely downloadable lecture slides and example code. The presentation is clean and simple, while also being fully compliant with the latest version of the language, including recent changes concerning applicative, monadic, foldable, and traversable types.
Python Workout presents 50 exercises designed to deepen the reader's skill with Python. Readers will not only tackle exercises using built-in data structures, but also more advanced techniques, such as functional programming, object-oriented programming, iterators, and generators. With each engaging challenge, readers will practice a new skill and learn how to apply it to everyday coding tasks. Key Features 50 hands-on exercises and solutions Basic Python sequence types Python dictionaries and sets Functional programming in Python Creating your own classes Working with Python objects Generator functions Intended for readers with basic Python skills. About the technology Python is a versatile, elegant, general purpose programming language. Essential for data analysis, web development, artificial intelligence, games, desktop apps, and more, Python skills are a hot commodity. Reuven M. Lerner, an independent consultant for more than two decades, teaches Python, data science, and Git to companies around the world. His Better developers newsletter and blog are read by thousands of Python developers each week. Reuven has written a monthly column, "At the Forge," for Linux Journal since 1996 and is a panellist on the weekly Freelancers Show podcast. Reuven lives with his wife and three children in Modi'in, Israel, and can be reached at https://lerner.co.il/ or on Twitter at @reuvenmlerner.
The latest edition of the definitive guide to the Ada language covers the full details of the core language Ada 2012 as updated by the 2016 ISO Corrigendum and introduces the key new features in Ada 2022. The book is in four parts. It begins by introducing the fundamental concepts for newcomers, before moving onto algorithmic aspects and then structural features such as OOP and multitasking. The fourth part gives details of the standard library and interaction with the external environment. Six complete executable programs illustrate the core features of the language in action. The book concludes with an appendix focussing on the new features in Ada 2022. These new features aid program proof and the efficient use of multicore architectures.
For courses in Java programming A clear and student-friendly way to teach the fundamentals of Java Starting Out with Java: Early Objects, 6th Edition features Tony Gaddis's accessible, step-by-step presentation which helps beginning students understand the important details necessary to become skilled programmers at an introductory level. Gaddis motivates the study of both programming skills and the Java programming language by presenting all the details needed to understand the "how" and the "why"-but never losing sight of the fact that most beginners struggle with this material. His approach is gradual and highly accessible, ensuring that students understand the logic behind developing high-quality programs. In Starting Out with Java: Early Objects, Gaddis looks at objects-the fundamentals of classes and methods-before covering procedural programming. As with all Gaddis texts, clear and easy-to-read code listings, concise and practical real world examples, and an abundance of exercises appear in every chapter. Updates to the 6th Edition include revised, improved problems throughout and three new chapters on JavaFX. Also Available with MyLab Programming. MyLab (TM) Programming is an online learning system designed to engage students and improve results. MyLab Programming consists of programming exercises correlated to the concepts and objectives in this book. Through practice exercises and immediate, personalized feedback, MyLab Programming improves the programming competence of beginning students who often struggle with the basic concepts of programming languages. Note: You are purchasing a standalone product; MyLab (TM) Programming does not come packaged with this content. Students, if interested in purchasing this title with MyLab (TM) Programming, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab (TM) Programming, search for: 0134543653 / 9780134543659 Starting Out with Java: Early Objects Plus MyProgrammingLab with Pearson eText -- Access Card Package, 6/e Package consists of: 0134447174 / 9780134447179 MyProgrammingLab with Pearson eText -- Access Card -- for Starting Out with Java: Early Objects 0134462017 / 9780134462011 Starting Out with Java: Early Objects Students can use the URL and phone number below to help answer their questions: http://247pearsoned.custhelp.com/app/home 800-677-6337
Designed for professionals and advanced students, Pointers On C provides a comprehensive resource for those needing in-depth coverage of the C programming language. An extensive explanation of pointer basics and a thorough exploration of their advanced features allows programmers to incorporate the power of pointers into their C programs. Complete coverage, detailed explanations of C programming idioms, and thorough discussion of advanced topics makes Pointers On C a valuable tutorial and reference for students and professionals alike.
CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you'll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA's parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debugging Creating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA's shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations
Develop Android apps with Kotlin to create more elegant programs than the Java equivalent. This revised book covers the various aspects of a modern Android app that professionals are expected to encounter. You'll use the latest Kotlin APIs as made available in most recent versions of the Android SDK. There are chapters dealing with all the important aspects of the Android platform, including GUI design, file- and data-handling, coping with phone calls, multimedia apps, interaction with location and mapping services, monetizing apps, and much more. Jetpack will also be covered. It is a suite of libraries to help developers follow best practices, reduce boilerplate code, and write code that works consistently across Android versions and devices. Pro Android with Kotlin, Second Edition is an invaluable source for developers wanting to build real-world, state-of-the-art Android apps for modern Android devices using the Kotlin programming language and its APIs as available in the modern Android SDK. After reading this book, you'll come away with the skills and techniques to build modern Android apps that you can sell on Google Play. Free source code is available on this book's Github page as well. What You Will Learn Integrate activities, such as intents, services, notifications and more, into your Android apps Build UIs in Android using layouts, widgets, lists, menus, and action bars Deal with data in your Android apps using data persistence and cloud access Design for different Android devices Create multimedia apps in Android Secure, deploy, and monetize your Android apps Who This Book Is ForProfessional Android app developers. |
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