Название: Java Generics and Collections: Fundamentals and Recommended Practices, 2nd Edition (Sixth Early Release)
Автор: Maurice Naftalin, Philip Wadler
Издательство: O'Reilly Media, Inc.
Год: 2025-03-13
Страниц: 371
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Java Generics and Collections has been the go-to guide to generics for more than a decade. This second edition covers Java 21, providing a clear guide to generics from their most common uses to the strangest corner cases, giving you everything you need to know to use and write generic APIs effectively. It covers the collections library thoroughly, so you'll always know how and when to use each collection for any given task. And it explains stream processing, so you'll know which model to use and how they interoperate to get the best out of the platform library. This book is intended for everyone who knows something about Java, and would like to find out more. It’s not a Java tutorial, so we assume knowledge of basic Java concepts like classes, static and instance methods, and so on. We use the syntax of Java 21, but most syntax features associated specifically with generics are explained in the text.

Название: Cultural Data Science: An Introduction to R
Автор: Harald Klinke
Издательство: Springer
Год: 2025
Страниц: 163
Язык: английский
Формат: pdf
Размер: 16.9 MB

This book addresses growing demand in the visual humanities for foundational knowledge in data analysis, image processing, and Artificial Intelligence (AI). Intended for readers without prior technical knowledge, its eighteen chapters introduce key concepts in Data Science through examples from art history, visual computing, and cloud technologies. For advanced readers, it explores how digital methods enhance our understanding of our cultural past. Focusing on image-based humanities research, the book demonstrates practical applications using open source software such as R, RStudio, and ImageMagick, along with open data sets from institutions like the MoMA, the Met, and the Rijksmuseum. To effectively analyze data, the choice of means is crucial. In this book, we are using the programming language R as a strategic choice, since it offers distinct advantages over alternative means. R, being an open-source language, accommodates a wide spectrum of data analysis tasks.

Название: AutoCAD 2026: A Power Guide for Beginners and Intermediate Users
Автор: Sandeep Dogra
Издательство: CADArtifex
Год: 2024
Формат: pdf, epub
Страниц: 656
Размер: 65.6 Мб
Язык: английский

AutoCAD 2026: A Power Guide for Beginners and Intermediate Users textbook is designed for instructor-led courses as well as for self-paced learning. It is intended to help engineers, designers, and CAD operators interested in learning AutoCAD to create 2D engineering drawings as well as 3D Models. This textbook is a great help for new AutoCAD users and a great teaching aid for classroom training. The textbook consists of 13 chapters, and a total of 552 pages covering major workspaces of AutoCAD such as Drafting & Annotation and 3D Modeling, teaching you to use AutoCAD software for creating, editing, plotting, and managing real-world 2D engineering drawings and 3D Models.

Название: Язык Java. Основы объектно ориентированного программирования
Автор: А. С. Кравчук, А. И. Кравчук, Е. В. Кремень
Издательство: Минск : БГУ
Год: 2023
Формат: pdf
Страниц: 223
Размер: 11,47 Мб
Язык: русский

Рассматриваются классы, интерфейсы, перечисления и записи, а также различные аспекты работы с ними. Подробно описывается механизм наследования и клонирования, даются основы построения диаграмм классов. В каждой теме приводится необходимый теоретический материал и код программ, что существенно ускоряет усвоение материала.

Название: Cracking the Python Coding Interview: A Comprehensive Guide to Algorithmic Problem Solving
Автор: Aarav Joshi
Издательство: 101 Books
Год: 2025
Страниц: 1669
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

"Cracking the Python Coding Interview: A Comprehensive Guide to Algorithmic Problem Solving" is a cutting-edge resource designed for Python developers preparing for technical interviews in 2025. This comprehensive guide covers essential coding patterns and problem-solving techniques specifically tailored for Python interviews at top tech companies and startups. The book features 15 meticulously structured chapters that progress from Python fundamentals to advanced data structures, algorithmic patterns, and real-world interview scenarios. Each chapter contains detailed explanations, multiple approaches to solving problems, time and space complexity analyses, and practical implementation tips. Whether you're a beginner or experienced developer, this guide provides the tools to master Python-specific interview challenges, optimize your solutions, and communicate your thought process effectively to interviewers.

Название: Docker. Вводный курс
Автор: Кейн Ш.П.
Издательство: Астана: АЛИСТ
Год: 2024
Формат: pdf
Страниц: 351
Размер: 21 mb
Язык: Русский

Книга подробно описывает инструментарий Docker и возможности использования контейнеров для развертывания программного обеспечения. Рассказано об интеграции Docker и контейнеров Linux с облачными сервисами и Kubernetes. Описаны методы сборки образов Open Container Initiative (OCI), развертывания и администрирования образов с использованием командной строки. Показано, как образы OCI упрощают управление зависимостями и ускоряют процесс развертывания приложений. Даны практические рекомендации по настройке и тестированию контейнеров, подробно рассмотрены инструменты оркестрации, обеспечения безопасности и конфигурирования Docker. В третьем издании особое внимание уделено инструменту BuildKit, поддержке мультиархитектурных образов, а также контейнеров в режиме rootless.

Название: Continuous Deployment for Java Apps: Mastering Jenkins and Docker
Автор: Peter Jones
Издательство: NOB TREX L.L.C.
Год: September 13, 2024
Страниц: 278
Язык: английский
Формат: pdf, epub (true)
Размер: 10.8 MB

"Continuous Deployment for Java Apps: Mastering Jenkins and Docker" is an indispensable guide for software developers, DevOps engineers, and IT professionals aiming to enhance their proficiency in cutting-edge deployment technologies. This comprehensive resource delves deeply into continuous deployment, with a special focus on Java applications and harnessing the capabilities of Jenkins and Docker—two pivotal tools in the modern DevOps landscape. The book provides a complete walkthrough—from setting up a robust development environment to mastering containerization and automation. You will learn how to prepare, build, test, and deploy Java applications seamlessly. Each chapter offers meticulous guidance on configuring Jenkins for automation, building Docker containers optimized for Java, managing staging environments, and addressing many other critical aspects.

Название: Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build Intelligent Systems (Early Release)
Автор: Aurélien Geron
Издательство: O’Reilly Media, Inc.
Год: 2025-05-15
Страниц: 399
Язык: английский
Формат: epub (true)
Размер: 39.96 MB

The potential of Machine Learning today is extraordinary, yet many aspiring developers and tech professionals find themselves daunted by its complexity. Perhaps you're ready to jump in, but you're unsure where or how to begin. Whether you're looking to enhance your skill set and apply machine learning to real-world projects or are simply curious about how AI systems function, this book is your jumping-off place. In a way that's approachable yet deeply informative, author Aurelien Geron delivers the ultimate introductory guide to Machine Learning and Deep Learning. With a focus on clear explanations and real-world Python examples, the book takes you through cutting-edge tools like Scikit-learn and PyTorch—from basic regression techniques to advanced neural networks like transformers and generative adversarial networks. Whether you're a student, professional, or hobbyist, you'll gain the skills to begin building intelligent systems.

Название: Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python, 2nd Edition
Автор: Joseph Awange, Béla Paláncz, Lajos Völgyesi
Издательство: Springer
Год: 2025
Страниц: 471
Язык: английский
Формат: pdf (true)
Размер: 65.4 MB

This second edition of the book that targets those in computer algebra and Artificial Intelligence introduces Black Hole algorithm that is essential for optimizing hyperparameters, an important task in Machine Learning where mostly, stochastic global methods are used as well as ChatGPT, a novel and in the last few years, very popular Generative AI technology. In addition, fisher discriminant, a linear discriminant that can provide an optimal separation of objects, and the conversion of time series into images thereby making it possible to employ convolution neural network to classify time series effectively are presented. Computer vision, a multidisciplinary field that is broadly a subfield of artificial intelligence and Machine Learning has as one of its goals the extraction of useful information from images. A basic problem in computer vision, therefore, is to try to understand, i.e., “see” the structure of the real world from a given set of images through use of specialized methods and general learning algorithms. In this book, we employ Python and Mathematica as well as their blending, since Python code can be run from Mathematica directly.

Название: Safety Assurance under Uncertainties: From Software to Cyber-Physical/Machine Learning Systems
Автор: Ichiro Hasuo, Fuyuki Ishikawa
Издательство: CRC Press
Год: 2025
Страниц: 366
Язык: английский
Формат: True PDF, True EPUB
Размер: 41.0 MB, 17.2 MB

Safety assurance of software systems has never been as imminent a problem as it is today. Practitioners and researchers who work on the problem face a challenge unique to modern software systems: uncertainties. For one, the cyber-physical nature of modern software systems as exemplified by automated driving systems mandates environmental uncertainties to be addressed and the resulting hazards to be mitigated. Besides, the abundance of statistical Machine Learning components massive numerical computing units for statistical reasoning such as deep neural networks make systems hard to explain, understand, analyze or verify. Testing is an “activity in which a system or component is executed under specified conditions, the results are observed or recorded, and an evaluation is made of some aspect of the system or component”. Testing has been one of the key activities for quality assurance in software-intensive systems. The recent advance of Machine Learning (ML) techniques, especially Deep Learning, has led to active investigation towards their industrial applications. Beforehand, ML techniques were target of laboratory research and the primary concern was on the prediction performance.