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Категория: КНИГИ » ПРОГРАММИРОВАНИЕ
Computational Stochastic Programming: Models, Algorithms, and Implementation
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Название: Computational Stochastic Programming: Models, Algorithms, and Implementation
Автор: Lewis Ntaimo
Издательство: Springer
Год: 2024
Страниц: 518
Язык: английский
Формат: pdf (true), epub
Размер: 40.5 MB

This book provides a foundation in stochastic, linear, and mixed-integer programming algorithms with a focus on practical computer algorithm implementation. The purpose of this book is to provide a foundational and thorough treatment of the subject with a focus on models and algorithms and their computer implementation. The book’s most important features include a focus on both risk-neutral and risk-averse models, a variety of real-life example applications of stochastic programming, decomposition algorithms, detailed illustrative numerical examples of the models and algorithms, and an emphasis on computational experimentation. With a focus on both theory and implementation of the models and algorithms for solving practical optimization problems, this monograph is suitable for readers with fundamental knowledge of linear programming, elementary analysis, probability and statistics, and some computer programming background. Several examples of stochastic programming applications areincluded, providing numerical examples to illustrate the models and algorithms for both stochastic linear and mixed-integer programming, and showing the reader how to implement the models and algorithms using computer software.


Категория: КНИГИ » ПРОГРАММИРОВАНИЕ
Methodologies, Frameworks, and Applications of Machine Learning
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Название: Methodologies, Frameworks, and Applications of Machine Learning
Автор: Pramod Kumar Srivastava, Ashok Kumar Yadav
Издательство: IGI Global
Год: 2024
Страниц: 315
Язык: английский
Формат: pdf (true), epub
Размер: 36.4 MB

In the ever-evolving landscape of technology, Machine Learning stands as a beacon of innovation with the potential to reshape industries and redefine our daily lives. As editors of this comprehensive reference book, Methodologies, Frameworks, and Applications of Machine Learning, we are thrilled to present a compendium that encapsulates the essence of the latest advancements, theoretical foundations, and practical applications in the realm of Machine Learning. Technology is constantly evolving, and Machine Learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest Machine Learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine Learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. The Chapter 2 focuses on practical implementations of Machine Learning projects using Scikit-learn and TensorFlow libraries in Python. Four distinct projects unfold, each addressing classification, regression, and image classification problems. The step-by-step walkthrough covers model evaluation using classical Machine Learning techniques and deep neural networks.


Категория: КНИГИ » ПРОГРАММИРОВАНИЕ
Jetpack Compose 1.5 Essentials: Developing Android Apps with Jetpack Compose 1.5, Android Studio, and Kotlin
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Название: Jetpack Compose 1.5 Essentials: Developing Android Apps with Jetpack Compose 1.5, Android Studio, and Kotlin
Автор: Neil Smyth
Издательство: Payload Media, Inc.
Год: 2024
Страниц: 636
Язык: английский
Формат: epub
Размер: 10.5 MB

This book teaches you how to build Android applications using Jetpack Compose 1.5, Android Studio Hedgehog (2023.1.1), Material Design 3, and the Kotlin programming language. The book begins with the basics by explaining how to set up an Android Studio development environment. The book also includes in-depth chapters introducing the Kotlin programming language, including data types, operators, control flow, functions, lambdas, coroutines, and object-oriented programming. If you are new to Kotlin programming, the entire book is appropriate for you. An introduction to the key concepts of Jetpack Compose and Android project architecture is followed by a guided tour of Android Studio in Compose development mode. The book also covers the creation of custom Composables and explains how functions are combined to create user interface layouts, including row, column, box, flow, pager, and list components. Other topics covered include data handling using state properties and key user interface design concepts such as modifiers, navigation bars, and user interface navigation. Additional chapters explore building your own reusable custom layout components, securing your apps with Biometric authentication, and integrating Google Maps. The book covers graphics drawing, user interface animation, transitions, Kotlin Flows, and gesture handling.


Категория: КНИГИ » ПРОГРАММИРОВАНИЕ
Robust Machine Learning Distributed Methods for Safe AI
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Название: Robust Machine Learning Distributed Methods for Safe AI
Автор: Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2024
Страниц: 180
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Today, Machine Learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure. This could, for example, result from hardware and software bugs, data poisoning or a malicious player controlling a subset of the machines. This book explains in simple terms what it means for a distributed Machine Learning scheme to be robust to these threats, and how to build provably robust Machine Learning algorithms. Studying the robustness of Machine Learning algorithms is a necessity given the ubiquity of these algorithms in both the private and public sectors. Accordingly, over the past few years, we have witnessed a rapid growth in the number of articles published on the robustness of distributed Machine Learning algorithms. We believe it is time to provide a clear foundation to this emerging and dynamic field. By gathering the existing knowledge and democratizing the concept of robustness, the book provides the basis for a new generation of reliable and safe Machine Learning schemes. In addition to introducing the problem of robustness in modern Machine Learning algorithms, the book will equip readers with essential skills for designing distributed learning algorithms with enhanced robustness. This book is intended for students, researchers, and practitioners interested in AI systems in general, and in Machine Learning schemes in particular. The book requires certain basic prerequisites in linear algebra, calculus, and probability. Some understanding of computer architectures and networking infrastructures would be helpful.


Категория: КНИГИ » ПРОГРАММИРОВАНИЕ
Modern API Design with gRPC: Efficient Solutions to Design Modern APIs with gRPC Using Golang for Scalable Distributed Systems
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Название: Modern API Design with gRPC: Efficient Solutions to Design Modern APIs with gRPC Using Golang for Scalable Distributed Systems
Автор: Hitesh Pattanayak
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 331
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

Elevate Your Development with Effortless and Efficient API Communication. “Modern API Design with gRPC” is a definitive guide that empowers developers to leverage the full potential of gRPC in constructing efficient and scalable distributed systems. Beginning with an exploration of API evolution and its significance in software development, the book seamlessly transitions into the core concepts of gRPC architecture, protocol buffers, and stubs. Through practical examples and clear instructions, readers embark on a journey to establish their first gRPC server and client, laying a solid groundwork for further exploration. An API, or ‘Application Programming Interface,’ serves as a bridge between software components. I personally perceive the origin of APIs in the pursuit of ‘Code Reusability,’ akin to the motivation behind crafting functions. What sets APIs apart from functions is their inherent ‘Remote-ness,’ where APIs are stationed at network-accessible locations. This book caters to intermediate to advanced software developers and programmers aiming to enhance their expertise in modern API development using gRPC. Prior familiarity with fundamental software development concepts and proficiency in at least one programming language such as C++, Python, Ruby, Objective-C, PHP, C# are recommended to fully comprehend the concepts presented in this guide.


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Coding For Beginners - 18th Edition, 2024
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Название: Coding For Beginners - 18th Edition, 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 46.8 MB

Coding For Beginners - это первый и единственный выбор, если вы новичок и хотите узнать все, что вам нужно для начала работы с кодированием и программированием. Это независимое руководство наполнено полезными рекомендациями и пошаговыми полностью иллюстрированными учебниками, написанными на простом и понятном английском языке. На страницах этого нового руководства вы узнаете все, что вам нужно знать о создании собственных удивительных приложений. С этим неофициальным руководством ни одна проблема не будет неразрешимой, ни один вопрос не останется без ответа, пока вы учитесь, изучаете и совершенствуете свои навыки программирования.


Категория: КНИГИ » ПРОГРАММИРОВАНИЕ
Handbook of Truly Concurrent Process Algebra
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Название: Handbook of Truly Concurrent Process Algebra
Автор: Yong Wang
Издательство: Morgan Kaufmann/Elsevier
Год: 2024
Страниц: 648
Язык: английский
Формат: pdf (true)
Размер: 15.0 MB

Handbook of Truly Concurrent Process Algebra provides readers with a detailed and in-depth explanation of the algebra used for concurrent computing. This complete handbook is divided into five Parts: Algebraic Theory for Reversible Computing, Probabilistic Process Algebra for True Concurrency, Actors – A Process Algebra-Based Approach, Secure Process Algebra, and Verification of Patterns. The author demonstrates actor models which are captured using the following characteristics: Concurrency, Asynchrony, Uniqueness, Concentration, Communication Dependency, Abstraction, and Persistence. Every pattern is detailed according to a regular format to be understood and utilized easily, which includes introduction to a pattern and its verifications. Patterns of the vertical domains are also provided, including the domains of networked objects and resource management. To help readers develop and implement the software patterns scientifically, the pattern languages are also presented. Reversible computing is an interesting topic in Computer Science. Reversible computing has been used in many area, such as quantum computing, transactions in databases, and business transactions. In these application areas, there are two aspects of reversible computing: one is that there is a corresponding reverse atomic action for each atomic action, so it is reversible at the level of atomic action; the other is in program logic, for the forward logic is important and the reverse logic is important too. The relation between the forward logic and reverse logic is the main content of reversible computing.


Категория: КНИГИ » ПРОГРАММИРОВАНИЕ
Synthetic Data and Generative AI
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Название: Synthetic Data and Generative AI
Автор: Vincent Granville
Издательство: Morgan Kaufmann/Elsevier
Год: 2024
Страниц: 410
Язык: английский
Формат: pdf (true), epub
Размер: 19.1 MB, 43.9 MB

Synthetic Data and Generative AI covers the foundations of Machine Learning, with modern approaches to solving complex problems and the systematic generation and use of synthetic data. Emphasis is on scalability, automation, testing, optimizing, and interpretability (explainable AI). For instance, regression techniques – including logistic and Lasso – are presented as a single method, without using advanced linear algebra. Confidence regions and prediction intervals are built using parametric bootstrap, without statistical models or probability distributions. Models (including generative models and mixtures) are mostly used to create rich synthetic data to test and benchmark various methods. I provide Python code and synthetic data generators for replication purposes.


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Python Asynchronous Programming for Beginners: Write Faster, More Responsive Python Applications!
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Название: Python Asynchronous Programming for Beginners: Write Faster, More Responsive Python Applications! The Beginner's Guide to Async/Await! From Fundamentals to Real-world Applications
Автор: Katie Millie
Издательство: Independently published
Серия: Python Trailblazer’s Bible
Год: 2024
Страниц: 154
Язык: английский
Формат: pdf
Размер: 27.0 MB

Python Asyncio for Beginners: Conquer Responsiveness and Build Blazing-Fast Apps. Imagine a world where your Python applications respond instantly, handling multiple tasks with ease. No more sluggish interfaces or frustrated users. Python Asynchronous Programming for Beginners is your launchpad to this future. This book isn't a dusty textbook. It's your interactive coding buddy, designed specifically for beginners. Whether you're a complete novice or have some Python experience, we'll guide you from the ground up. You'll learn to master asynchronous programming, the secret weapon for building modern, lightning-fast Python applications. Solid Python Foundations: We'll ensure you have a strong grasp of Python basics like variables, data types, control flow, and functions before diving into asynchronous concepts. Demystifying Asynchronous Programming: Uncover the core principles of this powerful technique, including concurrency, non-blocking I/O, and event loops. Mastering asyncio: The asyncio library is your asynchronous programming toolkit. We'll guide you through its functionalities, from tasks and coroutines to managing asynchronous operations with ease. Conquering Async/Await Syntax: Learn how to write asynchronous code using the powerful async/await keywords. Chaining asynchronous calls and handling results will become second nature. Building Asynchronous Applications: The fun part! We'll guide you through building real-world applications, like making lightning-fast web requests or creating dynamic user experiences.


Категория: КНИГИ » ПРОГРАММИРОВАНИЕ
Introduction to Artificial Intelligence (AI)
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Название: Introduction to Artificial Intelligence (AI)
Автор: Ahmed Banafa
Издательство: River Publishers
Год: 2024
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Introduction to Artificial Intelligence (AI) provides a comprehensive overview of the latest trends in Artificial Intelligence. The book covers the state of the art in AI research, including Machine Learning, natural language processing (NLP), computer vision, and robotics. The book offers a forward-looking perspective on the future of AI, exploring the emerging trends and applications that are likely to shape the next decade of AI innovation. It also provides practical guidance for businesses and individuals on how to leverage the power of AI to create new products, services, and opportunities. Artificial Intelligence (AI) is a term that refers to the capability of machines or computer programs to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. The field of AI has been around for several decades, but recent advances in technology have led to a rapid increase in its capabilities and applications. In this chapter, we will explore what AI is, how it works, and its current and potential future applications.