Название: Quantum Software: Aspects of Theory and System Design
Автор: Iaakov Exman, Ricardo Pérez-Castillo, Mario Piattini, Michael Felderer
Издательство: Springer
Год: 2024
Страниц: 358
Язык: английский
Формат: pdf (true)
Размер: 40.8 MB

This book explains the state of the art in Quantum Software engineering and design, independent from a specific hardware. It deals with quantum software theoretical aspects and with classical software engineering concepts like agile development approaches, validation, measurement, and deployment applied in a quantum or hybrid environment, and is complemented by a number of various industry applications. After an introductory chapter overviewing the contents of the subsequent chapters, the book is composed of three parts. It starts with a theoretical part on quantum software, as a bold declaration that quantum software theory is deep and valuable independent from the existence of specific quantum hardware. It is based upon the claim that quantum software is the more general theory subsuming classical and hybrid software system theories. The second, more extensive part deals with quantum software system and engineering design. Its quality follows from the comparison of the broad diversity of sometimes conflicting views. Moreover, the variety of approaches to design, enable the reader to make a well-pondered rational choice of preference. The book concludes with a third part, referring to multiple software applications and corresponding laboratory experiences, in order to understand their implications in practice and avoid repeating past mistakes. This book should be of interest to industry professionals and researchers in academia, who are either producing or applying quantum software systems in their work or are considering their potential utility in the future. Furthermore, this text could be beneficial for practitioners already experienced with classical software engineering who desire to understand the fundamentals of quantum software, including the underlying technology, programming techniques, and possible applications.

Название: AI and Digital Technology for Oil and Gas Fields
Автор: Niladri Kumar Mitra
Издательство: CRC Press
Год: 2025
Страниц: 258
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book tries to introduce Artificial Intelligence (AI) as the ability of a computer or a robot controlled by a computer to perform tasks that humans usually do because they require human intelligence and discernment. The primary objective of AI (also called heuristic programming, machine intelligence, or the simulation of cognitive behavior) is to enable computers to perform such intellectual tasks as decision-making, problem-solving, perception, and understanding human communication (in any language, and translating them). AI is a theory and development of computer systems that can perform tasks that normally require human intelligence. Speech recognition, decision-making, and visual perception, for example, are features of human intelligence that AI may possess. AI is also dipping into the digital oilfield well to leverage the latest advancement in intelligent visual monitoring technology to give companies the ability to limit remote site visits while reducing operational expenditure and mitigating safety and environmental risks. Python is one of the specific software programming languages used by various software developers. Being one of the best-known programming languages for AI and neural networks, Python has taken a big lead. AI, in combination with Python, is one of the best tools in the operating software system. Python, with its rich technology competency, has an extensive set of libraries for AI and ML. Some of them are Keras, TensorFlow, and Scikit-learn for ML, and NumPy for high-performance scientific computing and data analysis software.

Название: Разработка корпоративных Java-приложений с помощью J2EE и UML
Автор: Амриш Кэри, Ахмед Хавар
Издательство: Вильямс
Год: 2002
Страниц: 272
Формат: djvu
Размер: 14 мб
Качество: хорошее
Язык: русский

Для разработки сложного программного обеспечения недостаточно просто написать огромное количество кода. Разработчик или руководитель проекта должен уметь применять на практике методы архитектурного построения, анализа и проектирования, процессы разработки, визуальное моделирование и базовые технологии.

Название: Artificial Intelligence Solutions for Cyber-Physical Systems
Автор: Pushan Kumar Dutta, Pethuru Raj, B. Sundaravadivazhagan, Chithirai Pon Selvan
Издательство: CRC Press
Год: 2025
Страниц: 465
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Smart manufacturing environments are revolutionizing the industrial sector by integrating advanced technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), and robotics, to achieve higher levels of efficiency, productivity, and safety. However, the increasing complexity and interconnectedness of these systems also introduce new security challenges that must be addressed to ensure the safety of human workers and the integrity of manufacturing processes. Key topics include risk assessment methodologies, secure communication protocols, and the development of standard specifications to guide the design and implementation of HCPS. Recent research highlights the importance of adopting a multi-layered approach to security, encompassing physical, network, and application layers. Furthermore, the integration of AI and Machine Learning techniques enables real-time monitoring and analysis of system vulnerabilities, as well as the development of adaptive security measures. Cyber‑physical systems (CPS) are systems that tightly integrate physical components with computational and networking elements. They are becoming increasingly prevalent in a wide range of applications, such as transportation, healthcare, and manufacturing. Artificial Intelligence (AI) has the potential to significantly improve the performance and capabilities of CPS. Deep Learning and neural networks are subfields of AI and Machine Learning (ML) that have gained significant attention and success in recent years. They involve the use of computational models inspired by the structure and function of the human brain to process and analyse complex data. Deep Learning is a subfield of Machine Learning that focuses on employing neural networks with numerous hidden layers to model and solve complex patterns in data. It has had great success in a number of fields, including speech and picture identification, natural language processing, and autonomous driving.

Название: Python для всех
Автор: Северанс Ч. Р.
Издательство: ДMK
Год: 2021 (2022)
Cтраниц: 262
Формат: pdf
Размер: 14 мб
Язык: русский

Python — простой в изучении и практическом использовании язык программирования, который свободно доступен на компьютерах под управлением Mac OS, Windows и Linux. Изучив Python, вы сможете использовать его в своей профессиональной деятельности, не покупая какое-либо программное обеспечение.

Название: Leveraging Artificial Intelligence (AI) Competencies for Next-Generation Cybersecurity Solutions
Автор: Pethuru Raj, B. Sundaravadivazhagan, V. Kavitha
Издательство: Apple Academic Press, CRC Press
Год: 2025
Страниц: 580
Язык: английский
Формат: pdf (true)
Размер: 32.6 MB

Modern enterprises are facing growing cybersecurity issues due to the massive volume of security-related data they generate over time. AI systems can be developed to resolve a range of these issues with comparative ease. This new book describes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help eliminate them. With chapters from industry and security experts, this volume discribes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help elimintate them. With chapters from industry and security experts, this volume discusses the many new and emerging AI technologies and approaches that can be harnessed to combat cyberattacks, including Big Data analytics techniques, deep neural networks, cloud computer networks, convolutional neural networks, IoT edge devices, Machine Learning approaches, Deep Learning, blockchain technology, convolutional neural networks, and more. Machine and Deep Learning (ML/DL) models are being established and deployed to receive and analyze all kinds of log and security-related event data instantaneously to supply actionable insights and to activate the appropriate countermeasures in time. Therefore, any cybersecurity attack can be nipped in the budding stage. This book, Leveraging the Artificial Intelligence Competencies for Next-Generation Cybersecurity Solutions, illustrates how AI is a futuristic and flexible technology that can be effectively used for tackling the growing menace of cybercriminals. It clearly demystifies the unique contributions of AI algorithms, models, frameworks, and libraries in nullifying the cyberattacks.

Название: Безопасные и надежные системы: Лучшие практики проектирования, внедрения и обслуживания как в Google
Автор: Хизер Адкинс, Бетси Бейер, Пол Бланкиншип, Петр Левандовски, Ана Опреа, Адам Стабблфилд
Издательство: Питер
Год: 2025
Формат: pdf
Страниц: 592
Размер: 23,9 Мб
Язык: русский

Может ли быть надежной небезопасная система? Можно ли считать безопасной ненадежную систему? Безопасность имеет решающее значение для разработки и эксплуатации масштабируемых систем в реальных условиях, поскольку вносит важный вклад в качество, производительность и доступность продукта. В этой книге эксперты Google делятся передовым опытом, позволяющим разрабатывать масштабируемые и надежные системы, которые действительно будут безопасны. Вам уже знакомы два бестселлера, написанные разработчиками из Google — «Site Reliability Engineering. Надежность и безотказность как в Google» и «Site Reliability Workbook: практическое применение», значит, вы понимаете, что только неуклонное следование жизненному циклу обслуживания позволяет успешно создавать, развертывать и поддерживать программные системы. Сейчас же мы предлагаем взглянуть на проектирование, реализацию и обслуживание систем с точки зрения практиков, специализирующихся на безопасности и надежности.

Название: Large Language Models: A Deep Dive: Bridging Theory and Practice
Автор: Uday Kamath, Kevin Keenan, Garrett Somers
Издательство: Springer
Год: 2024
Страниц: 496
Язык: английский
Формат: pdf (true)
Размер: 30.7 MB

Large Language Models (LLMs) have emerged as a cornerstone technology, transforming how we interact with information and redefining the boundaries of Artificial Intelligence (AI). LLMs offer an unprecedented ability to understand, generate, and interact with human language in an intuitive and insightful manner, leading to transformative applications across domains like content creation, chatbots, search engines, and research tools. This book provides an authoritative exploration of the design, training, evolution, and application of LLMs. It begins with an overview of pre-trained language models and Transformer architectures, laying the groundwork for understanding prompt-based learning techniques. Next, it dives into methods for fine-tuning LLMs, integrating reinforcement learning for value alignment, and the convergence of LLMs with computer vision, robotics, and speech processing. The book strongly emphasizes practical applications, detailing real-world use cases such as conversational chatbots, retrieval-augmented generation (RAG), and code generation. These examples are carefully chosen to illustrate the diverse and impactful ways LLMs are being applied in various industries and scenarios. Not surprisingly, LLMs are highly competent at generating computer programming language and natural language. The most popular solution in this space is Github Copilot, which was designed to assist human programmers in developing software using computer code. Since it is the most popular solution in this space, below we will look at its core capabilities as an exemplar of the types of benefits that these types of LLM-enabled applications provide. Multiple programming language support allows developers to interoperate across coding languages efficiently. This capability is most useful in full-stack or specialist-domain application development, where multiple programming languages are used for different solution components. Imagine a full-stack developer writing data handling routines in jаvascript for the user interface. At the same time, Copilot suggests code blocks in Python for the back-end API that serves the data to the front-end.

Автор: Шилдт Герберт
Название: С++ для начинающих: Самоучитель
Серия: Шаг за шагом
Издательство: ЭКОМ Паблишерз
Год: 2013
Страниц: 640
Формат: DJVU, PDF
Размер: 41 МБ

Книга известного американского специалиста и популяризатора языков программирования, посвященная основам языка С++. Начиная с таких базовых понятий языка> как типы данных, массивы, строки,указатели и функции, книга охватывает также важнейшие элементы объёктно-ориентированного программирования - классы и объекты, наследование,' виртуальные функции, потоки ввода--вывода, исключения и шаблоны.

Название: Data Storytelling with Altair and AI (Final Release)
Автор: Angelica Lo Duca
Издательство: Manning Publications
Год: 2024
Страниц: 386
Язык: английский
Формат: pdf (true)
Размер: 11.1 MB

Great data presentations tell a story. Learn how to organize, visualize, and present data using Python, generative AI, and the cutting-edge Altair data visualization toolkit. Take the fast track to amazing data presentations! Data Storytelling with Altair and AI introduces a stack of useful tools and tried-and-tested methodologies that will rapidly increase your productivity, streamline the visualization process, and leave your audience inspired. Data Storytelling with Altair and AI teaches you how to turn raw data into effective, insightful data stories. You’ll learn exactly what goes into an effective data story, then combine your Python data skills with the Altair library and AI tools to rapidly create amazing visualizations. Your bosses and decision-makers will love your new presentations—and you’ll love how quick Generative AI makes the whole process! Every dataset tells a story. After you’ve cleaned, crunched, and organized the raw data, it’s your job to share its story in a way that connects with your audience. Python’s Altair data visualization library, combined with generative AI tools like Copilot and ChatGPT, provide an amazing toolbox for transforming numbers, code, text, and graphics into intuitive data presentations. For data analysts and data scientists experienced with Python. No previous knowledge of Altair or Generative AI required.