Название: Python Coding for Beginners - 18th Edition, 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 40.9 MB

"Программирование на Python для начинающих" - это первый и единственный выбор, если вы только начинаете и хотите узнать все, что вам нужно, чтобы начать программировать. Это независимое руководство наполнено полезными рекомендациями и пошаговыми полностью иллюстрированными примерами, написанными на простом и понятном английском языке. На страницах этого нового руководства вы узнаете все, что вам нужно знать о создании собственных потрясающих приложений. С этим неофициальным руководством по эксплуатации ни одна проблема не будет неразрешимой, ни один вопрос не останется без ответа, пока вы учитесь, изучаете и улучшаете свой пользовательский опыт.

Название: Практикум по объектно-ориентированному программированию
Автор: Бабушкина И. А., Окулов С. М.
Издательство: Лаборатория знаний
Год: 2020 - 5-е изд.
Cтраниц: 370
Формат: pdf (ocr)
Размер: 39 мб
Язык: русский

Практикум содержит материал для проведения занятий по объектно-ориентированному программированию в среде Delphi. Изложены основы теории объектно-ориентированного программирования, на базе которой изучаются возможности Delphi и отрабатываются технологии разработки различных приложений. Разобрано около 50 упражнений, приведено более 140 заданий для самостоятельной работы и 60 вопросов для контроля.

Название: Refactoring to Rust (MEAP v7)
Автор: Lily Mara
Издательство: Manning Publications
Год: 2024
Страниц: 338
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Get the speed and reliability of Rust libraries, functions, and high-performance features through incremental adoption without rewriting your codebase from scratch. Refactoring to Rust teaches you how to take advantage of Rust’s easy-to-use interoperating mechanisms. Learn practical code-mixing techniques like embedding Rust libraries into apps written in other languages. This practical guide emphasises techniques for incrementally refactoring performance-critical code to Rust while keeping the rest of your application in its original language. Rust is one of the most exciting new languages out there. Consistently rated as the “most loved” language by the Stack Overflow developer survey, many developers wonder what about Rust makes its users so happy. In our development jobs, it can be difficult to get management buy-in to start up a new service around a language that may never have been used at the company before. Instead, replacing a small part of performance-critical code with Rust might be a more effective first project. This book intends to give you the tools and skills required to make a surgical refactoring like this possible. The chapters in this book will take you through the areas where Rust differs the most from other languages, introduce you to embedding Rust within a C program, using the Py03 library to embed Rust in Python, as well as testing, profiling, and monitoring your refactored code to ensure that it’s performing within expectations. Refactoring to Rust is intended for developers that have some familiarity with Rust already.

Название: Meta-Heuristic Algorithms for Advanced Distributed Systems
Автор: Rohit Anand, Abhinav Juneja, Digvijay Pandey
Издательство: Wiley
Год: 2024
Страниц: 460
Язык: английский
Формат: pdf (true), epub
Размер: 14.0 MB

Discover a collection of meta-heuristic algorithms for distributed systems in different application domains. Meta-heuristic techniques are increasingly gaining favor as tools for optimizing distributed systems—generally, to enhance the utility and precision of database searches. Carefully applied, they can increase system effectiveness, streamline operations, and reduce cost. Since many of these techniques are derived from nature, they offer considerable scope for research and development, with the result that this field is growing rapidly. Meta-Heuristic Algorithms for Advanced Distributed Systems offers an overview of these techniques and their applications in various distributed systems. With strategies based on both global and local searching, it covers a wide range of key topics related to meta-heuristic algorithms. Those interested in the latest developments in distributed systems will find this book indispensable. Recent research on using Machine Learning (ML) to find effective, profitable, and adaptive metaheuristics has grown. Many stochastic and metaheuristic algorithms have delivered high-quality results and are cutting-edge optimization strategies. Meta-Heuristic Algorithms for Advanced Distributed Systems is ideal for academics and researchers studying distributed systems, their design, and their applications.

Название: Алгоритмы с нуля
Автор: Cuantum Technologies
Издательство: Питер
Год: 2024
Формат: PDF
Страниц: 258
Размер: 22 Mb
Язык: Русский

Погрузитесь в мир алгоритмов! Разберитесь в их принципах, особенностях проектирования и практического применения. Вы познакомитесь с различными видами алгоритмов, узнаете их сильные и слабые стороны, и поймете, в каких контекстах они лучше всего работают. На практических примерах увидите, как эти мощные инструменты используются для решения задач в информатике, анализе данных, искусственном интеллекте и других областях. Каждая глава содержит понятные объяснения, наглядные примеры и задачи, помогающие закрепить изученный материал. Особый акцент сделан на вычислительном мышлении и анализе эффективности алгоритмов — важнейших навыках в области современных технологий. Книга «Алгоритмы с нуля» послужит ценным ресурсом и для новичков, и для профессионалов, желающих отточить свои навыки.

Название: Enterprise Generative AI Well Architected Framework & Patterns: An Architect's Real-life Guide to Adopting Generative AI in Enterprises at Scale
Автор: Suvoraj Biswas, Moumita Biswas
Издательство: Independently published
Год: 2024
Страниц: 114
Язык: английский
Формат: True/Retail PDF EPUB
Размер: 17.1 MB

Welcome to the "Enterprise Generative AI Well Architected Framework & Patterns" a comprehensive step by step guide designed for Enterprise IT Professionals to explore the cutting-edge world of generative artificial intelligence (AI) systems within the context of enterprise applications. We have all witnessed how OpenAI has recently reshaped the digital landscape through the introduction of tools like ChatGPT, which gained a substantial user base surpassing all popular social media applications. ChatGPT has been powered by what we call Generative AI which not only has remarkable influence in the consumer sphere but also many Enterprises are adopting to solve many business challenges which previously appeared impossible. Generative AI is a form of Deep Learning system which is able to generate new original contents (texts or digital media - audio or Video or images). It uses the Machine Mearning algorithm and artificial neural networks to recognize the underlying pattern in the training data to predict new original contents without any human intervention or influences. This book is intended to provide readers with a clear understanding of the fundamental principles, methodologies, and best practices for implementing generative AI in large-scale enterprise environments. Whether you are a seasoned AI practitioner(Architects, Engineers / Engineering Managers or Product Managers) seeking to deepen your knowledge or an enterprise leader (VPs, CXOs, Founders) exploring the potential of Generative AI for your organization, this book offers valuable insights into leveraging the power of generative models effectively and responsibly.

Название: Postman Cookbook: Hand-picked Solutions and Techniques across API Design, Testing, Performance, Networking, Kubernetes and Integration
Автор: Oliver James
Издательство: GitforGits
Год: 2024
Страниц: 290
Язык: английский
Формат: pdf, azw3, epub (true), mobi
Размер: 10.1 MB

For developers, programmers, and DevOps engineers venturing into the hard world of API development, the "Postman Cookbook" becomes a must-read. This short solutions book offers recipes and troubleshooting approaches to address typical API lifecycle management challenges. Using Postman's rich features, readers of all skill levels will learn how to create APIs that will improve workflows, increase productivity, and lead to operational success. The book covers a wide range of topics, from the fundamentals of web-based communication to more complex topics including protocol stacks, secure communication protocols, and the dynamics of WebSockets interactions. The following sections cover advanced subjects such as custom protocol handling, network troubleshooting, and proxy management, allowing readers to confidently solve complex networking challenges. This book covers more than simply the technical aspects of Kubernetes. It discusses the influence of security measures, maximizing performance, and successful scaling solutions. These features are critical for microservice architectures and cloud-native apps. This book teaches early developers and programmers the foundations of API testing and development, including networking and protocols. Upon completion of this book, readers will have a thorough understanding of API development with Postman. They will be able to confidently handle the problems of modern computing.

Название: Artificial Intelligence: Advances, Ethics, and Strategies
Автор: James M. Nichols
Издательство: Nova Science Publishers
Серия: Computer Science, Technology and Applications
Год: 2024
Страниц: 242
Язык: английский
Формат: pdf (true)
Размер: 25.9 MB

The field of Artificial Intelligence (AI) is rapidly evolving, and one of the most exciting developments in recent years has been the emergence of generative models. These models have shown the ability to produce human-like language and even generate images, videos, and music. While the potential applications of generative models are vast and impressive, there are also serious concerns about the ethical implications of their use. As the potential of AI and generative models is explored, it is essential to consider the impact they may have on society. Generative Artificial Intelligence (GenAI) refers to AI systems, in particular those using Machine Learning (ML) and trained on large volumes of data, that are able to generate new content. In contrast, other AI systems may have a primary goal of classifying data, such as facial recognition image data, or making decisions, such as those used in autonomous vehicles. GenAI systems, when prompted (often by a user inputting text), can create various outputs, including text responses (e.g., OpenAI’s ChatGPT and Google’s Bard), images (e.g., Stability AI’s Stable Diffusion and Midjourney’s self-titled program), videos, computer code, or music.

Название: Artificial Intelligence: Background, Risks and Policies
Автор: Gary Dalton
Издательство: Nova Science Publishers
Серия: Computer Science, Technology and Applications
Год: 2024
Страниц: 280
Язык: английский
Формат: pdf (true)
Размер: 24.2 MB

The field of Artificial Intelligence (AI) has gone through multiple waves of advancement over the decades. Today, AI can broadly be thought of as computerized systems that work and react in ways commonly thought to require intelligence, such as the ability to learn, solve problems, and achieve goals under uncertain and varying conditions. The field encompasses a range of methodologies and application areas, including Machine Learning (ML), natural language processing, and robotics. AI holds potential benefits and opportunities, but also challenges and pitfalls. For example, AI technologies can accelerate and provide insights into data processing; augment human decision-making; optimize performance for complex tasks and systems; and improve safety for people in dangerous occupations. On the other hand, AI systems may perpetuate or amplify bias, may not yet be fully able to explain their decision-making, and often depend on vast datasets that are not widely accessible to facilitate research and development (R&D). Further, stakeholders have questioned the adequacy of human capital in both the public and private sectors to develop and work with AI, as well as the adequacy of current laws and regulations for dealing with societal and ethical issues that may arise. Together, such challenges can lead to an inability to fully assess and understand the operations and outputs of AI systems.

Название: Exploring Operations Research with R
Автор: Jim Duggan
Издательство: CRC Press
Год: 2024
Страниц: 396
Язык: английский
Формат: pdf (true)
Размер: 52.1 MB

Exploring Operations Research with R shows how the R programming language can be a valuable tool – and way of thinking – which can be successfully applied to the field of operations research (OR). This approach is centred on the idea of the future OR professional as someone who can combine knowledge of key OR techniques (e.g., simulation, linear programming, data science, and network science) with an understanding of R, including tools for data representation, manipulation, and analysis. The core aim of the book is to provide a self-contained introduction to R (both Base R and the tidyverse) and show how this knowledge can be applied to a range of OR challenges in the domains of public health, infectious disease, and energy generation, and thus provide a platform to develop actionable insights to support decision making. The central idea behind this book is that R is a valuable computational tool that can be applied to the field of operations research. R provides excellent features such as data representation, data manipulation, and data analysis. You will learn how to program and manipulate data in R, how to harness the power of R’s tidyverse, and observe how R can be used to support problem solving within the field of operations research. The book is primarily aimed at post-graduate students in operations research. With its coverage of R, the tidyverse, and applications in agent-based simulation and system dynamics, the book also supports continuing professional development for operations research practitioners. As R is presented from scratch, there are no prerequisites, although prior experience of a programming language would provide useful contextual knowledge.