Название: Object-Oriented Software Design in C++ (Final)
Автор: Ronald Mak
Издательство: Manning Publications
Год: 2024
Страниц: 520
Язык: английский
Формат: epub
Размер: 15.7 MB

Learn the fundamentals of Object-Oriented design by investigating good—and bad—code! Well-designed applications run more efficiently, have fewer bugs, and are easier to revise and maintain. Using an engaging “before-and-after” approach, Object-Oriented Software Design in C++ shows you exactly what bad software looks like and how to fix it with good design principles and patterns. Object-Oriented Software Design in C++ is a vital guide to building the kind of high performance applications delivered by the pros—all using industry-proven design principles and patterns. You’ll learn how to gather and analyze requirements so you’re building exactly what your client is looking for, backtrack mistakes with iterative development, and build a toolbox of design patterns that troubleshoot common issues with application architecture. The book’s accessible examples are written in C++ 17, but its universal principles can be applied to any object-oriented language. Object-Oriented Software Design in C++ introduces object-oriented design principles, practices, and patterns in clear, jargon-free language. The instantly-familiar before-and-after examples highlight the benefits of good design. Each chapter is full of friendly conversations that anticipate your questions and help point out the subtleties you might overlook. Along the way, you’ll pick up tips about idiomatic C++ style that will set your code apart. Examples are in C++ 17.

Название: Machine Learning with Noisy Labels: Definitions, Theory, Techniques and Solutions
Автор: Gustavo Carneiro
Издательство: Academic Press/Elsevier
Год: 2024
Страниц: 312
Язык: английский
Формат: epub
Размер: 43.5 MB

Machine Learning and Noisy Labels: Definitions, Theory, Techniques and Solutions provides an ideal introduction to Machine Learning with noisy labels that is suitable for senior undergraduates, post graduate students, researchers and practitioners using, and researching, Machine Learning methods. Most of the modern Machine Learning models based on Deep Learning techniques depend on carefully curated and cleanly labeled training sets to be reliably trained and deployed. However, the expensive labeling process involved in the acquisition of such training sets limits the number and size of datasets available to build new models, slowing down progress in the field. This book defines the different types of label noise, introduces the theory behind the problem, presents the main techniques that enable the effective use of noisy-label training sets, and explains the most accurate methods. The book starts by defining the noisy-label learning problem, then it introduces different types of label noise and the theory behind the problem. It also presents the main techniques and methods that enable the effective use of noisy-label training sets. With this book, the reader will have the tools to be able to understand, reproduce, and design regression, classification, segmentation, and detection models that can be trained with large-scale noisy-label training sets. Advanced Machine Learning courses that cover topics in learning with noisy-label and real-world datasets will greatly benefit from the insights provided in this book.

Название: Federated Learning: Theory and Practice
Автор: Lam M. Nguyen, Trong Nghia Hoang, Pin-Yu Chen
Издательство: Academic Press/Elsevier
Год: 2024
Страниц: 434
Язык: английский
Формат: epub
Размер: 23.4 MB

Federated Learning: Theory and Practice provides a holistic treatment to Federated Learning as a distributed learning system with various forms of decentralized data and features. Part I of the book begins with a broad overview of optimization fundamentals and modeling challenges, covering various aspects of communication efficiency, theoretical convergence, and security. Part II features emerging challenges stemming from many socially driven concerns of Federated Learning as a future public Machine Learning service. Part III concludes the book with a wide array of industrial applications of Federated Learning, as well as ethical considerations, showcasing its immense potential for driving innovation while safeguarding sensitive data. Federated Learning: Theory and Practice provides a comprehensive and accessible introduction to Federated Learning which is suitable for researchers and students in academia, and industrial practitioners who seek to leverage the latest advance in Machine Learning for their entrepreneurial endeavors. In our era of Big Data and the rapid advancement of Artificial Intelligence (AI), innovation and progress are often driven by harnessing the power of vast amounts of data. Yet, privacy concerns and data protection regulations have placed limitations on traditional centralized approaches to Machine Learning: While data are abundant, they often exist in small and isolated silos. The need for collaborative and privacy-preserving approaches to Machine Learning has therefore become more crucial than ever. In this context, Federated Learning (FL) has emerged as the de facto framework for distributed Machine Learning (ML) that preserves the privacy of data, especially in the proliferation of mobile and edge devices with their increasing capacity for storage and computation.

Название: Learn Ansible: Automate your cloud infrastructure, security configuration, and application deployment with Ansible
Автор: McKendrick Russ
Издательство: Packt
Год выхода: 2024
Страниц: 414
Формат: True PDF
Размер: 13,8 MB
Язык: английский

Learn Ansible is for system administrators, developers, and infrastructure engineers who want to implement infrastructure automation and configuration management using Ansible. The hands-on tutorials make this book ideal for both beginners as well as intermediate users looking to take their Ansible skills to the next level. Technology professionals working with public cloud platforms like AWS and Azure will also find valuable insights into automating deployments.

Название: Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG
Автор: Louis-François Bouchard, Louie Peters
Издательство: Towards AI, Inc.
Год: 2024
Страниц: 475
Язык: английский
Формат: epub (true)
Размер: 11.1 MB

With amazing feedback from industry leaders, this book is an end-to-end resource for anyone looking to enhance their skills or dive into the world of AI and develop their understanding of Generative AI and Large Language Models (LLMs). It explores various methods to adapt "foundational" LLMs to specific use cases with enhanced accuracy, reliability, and scalability. Written by over 10 people on our Team at Towards AI and curated by experts from Activeloop, LlamaIndex, Mila, and more, it is a roadmap to the tech stack of the future. Whether you're looking to enhance your skills or dive into the world of AI for the first time as a programmer or software student, our book is for you. From the basics of LLMs to mastering fine-tuning and RAG for scalable, reliable AI applications, we guide you every step of the way. The book aims to guide developers through creating LLM products ready for production, leveraging the potential of AI across various industries. It is tailored for readers with an intermediate knowledge of Python.

Название: Building Scalable Web Apps with Node.js and Express: Design and Develop a Robust, Scalable, High-Performance Web Application Using Node.js, Express.js, TypeScript, and Redis
Автор: Yamini Panchal, Ravi Kumar Gupta
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 382
Язык: английский
Формат: epub (true)
Размер: 43.8 MB

Easy API Design Using Express.js and Node.js (TypeScript). Embark on a transformative journey into the world of web development with the latest Node.js v20, Express.js frameworks and TypeScript. This comprehensive book empowers developers at all levels, from newcomers to seasoned professionals, by covering foundational to advanced topics through a single, cohesive example: a project management system. Beginning with an exploration of fundamentals, the book swiftly progresses to delve into TypeScript, equipping readers with the tools to enhance their applications with strong typing and modern jаvascript features. Readers will master the art of building RESTful APIs using Express.js, ensuring adherence to industry best practices in API design. The book dives into advanced topics like routing strategies, middleware implementation, MongoDB integration with Mongoose for efficient data management, and Redis for optimizing API performance through caching techniques. The final section of the book provides thorough guidance on asynchronous operations, Mocha and Chai testing strategies, AWS deployment, security practices, performance tuning, and real-world application scenarios, ensuring developers gain a holistic understanding of Node.js and Express.js development. From cumbersome setups for writing APIs to launching projects in just five minutes with Node.js and Express.js, developers have come a long way to witness revolutionary simplification in web development. If you are new to Node.js, this book offers a clear pathway to master backend development using Node.js, TypeScript, and Express.js. If you are already familiar with jаvascript or Node.js and aim to build scalable and efficient APIs, this book will elevate your skills, equipping you with the techniques needed for modern backend architecture.

Название: Building Micro-Frontends: Distributed Systems for the Frontend, 2nd Edition (Second Release)
Автор: Luca Mezzalira
Издательство: O’Reilly Media, Inc.
Год: 2024-06-24
Страниц: 149
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

What's the answer to today's increasingly complex applications? Micro-frontends. Inspired by the microservices model, this approach lets you break interfaces into separate features managed by different teams of developers. In this updated second edition, software architects, tech leads, and software developers will learn how to design, build, and deploy independent micro-frontends that compose unique frontend systems. Author Luca Mezzalira, principal serverless specialist solutions architect at AWS, shows you how micro-frontends enable agility within an organization, decentralize decision-making, and optimize for fast flow. This gives your organization technical flexibility and allows you to hire and retain a broad spectrum of talent. Micro-frontends also support distributed or colocated teams more efficiently. Pick up this book and learn how to get started with this technological breakthrough right away. In the long run, companies with large monoliths usually slow down all the operations needed to release any new feature, losing the great momentum they had at the beginning of a project where everything was easier and smaller with few complications and risks. Also, with monolithic applications, we have to test and deploy the entire codebase every single time, which comes with a higher chance of breaking the APIs in production, introducing new bugs, and making more mistakes, especially when the codebase is not rock solid or extensively tested. Solving these and many other challenges its staff faces, a company might move from complex monolith codebases to multiple smaller codebases and scoped domains called microservices.

Название: Программирование инженерных задач на базе использования алгоритмов циклической структуры на языке C в среде VS C++. Модуль 2
Автор: Алексеев Ю. Е., Куров А. В.
Издательство: МГТУ им. Баумана
Год: 2019
Cтраниц: 134
Формат: pdf
Размер: 17 мб
Язык: русский

Приведены краткие теоретические сведения по организации программ циклической структуры на примере алгоритмов вычисления сумм, произведений, суммы бесконечного ряда, определенного интеграла, уточнения корней уравнений. Рассмотрена организация вложенных циклов, показано решение таких задач, как вычисление определенного интеграла с заданной точностью, поиск наибольшего (наименьшего) значения функции с требуемой точностью, обработка матриц, сортировка элементов массива.

Название: The Nature of Code: Simulating Natural Systems with jаvascript
Автор: Daniel Shiffman
Издательство: No Starch Press
Год: 2024
Страниц: 640
Язык: английский
Формат: epub
Размер: 45.2 MB

All aboard The Coding Train! This beginner-friendly creative coding tutorial is designed to grow your skills in a fun, hands-on way as you build simulations of real-world phenomena with “The Coding Train” YouTube star Daniel Shiffman. What if you could re-create the awe-inspiring flocking patterns of birds or the hypnotic dance of fireflies—with code? For over a decade, The Nature of Code has empowered countless readers to do just that, bridging the gap between creative expression and programming. This innovative guide by Daniel Shiffman, creator of the beloved Coding Train, welcomes budding and seasoned programmers alike into a world where code meets playful creativity. This jаvascript-based edition of Shiffman’s groundbreaking work gently unfolds the mysteries of the natural world, turning complex topics like genetic algorithms, physics-based simulations, and neural networks into accessible and visually stunning creations. The p5.js library is a reimagining of the Processing creative coding environment for the modern web. I’m using it in this book for a number of reasons. For one, it’s an environment that I’m very familiar with. While the original Processing built on top of Java is my first love and still what I turn to when trying out a new idea, p5.js is what I now use for teaching many of my programming classes. It’s free, open source, and well suited to beginners, and because it’s jаvascript, everything runs right there in the web browser itself—no installation required. The prerequisites for understanding the material in this book could be stated as “one semester of programming instruction with p5.js, Processing, or any other creative coding environment.” That said, there’s no reason you couldn’t read this book having learned programming with a different language or development environment. NOTE: All examples are written with p5.js, a jаvascript library for creative coding, and are available on the book's website and its associated GitHub repository.

Название: Learning Analytics Methods and Tutorials: A Practical Guide Using R
Автор: Mohammed Saqr, Sonsoles López-Pernas
Издательство: Springer
Год: 2024
Страниц: 748
Язык: английский
Формат: pdf (true)
Размер: 26.3 MB

This comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field started. The book covers all important quantitative topics in education at large as well as the latest in learning analytics and education data mining. The book also goes deeper into advanced methods that are at the forefront of novel methodological innovations. Authors of the book include world-renowned learning analytics researchers, R package developers, and methodological experts from diverse fields offering an unprecedented interdisciplinary reference on novel topics that is hard to find elsewhere. The book starts with the basics of R as a programming language, the basics of data cleaning, data manipulation, statistics, and analytics. The core of the book explores various analytical approaches. Machine Learning (ML) methods receive well-deserved attention, including introductions to commonly used methods—specifically, predictive modeling and clustering. The book offers a comprehensive guide to data analysis methods for researchers and practitioners of all experience levels. It starts with the basics, equipping beginners with R programming and data analysis skills through chapters on data cleaning and exploration. These skills are fundamental for understanding student data and preparing it for further analysis. Even for experts, the book offers advanced methods while emphasizing the broader applicability of these techniques beyond education.