Название: Java Spring Boot: A Middle-Level Guide to Enhancing Microservices and RESTful APIs with Spring Boot
Автор: Henry Arias
Издательство: Independently published
Год: 2024
Страниц: 197
Язык: английский
Формат: epub
Размер: 10.1 MB

Unlock the full potential of Java Spring Boot with "Java Spring Boot: A Middle-Level Guide to Enhancing Microservices and RESTful APIs with Spring Boot." This expertly crafted guide is designed for developers who have a basic understanding of Spring Boot and are ready to elevate their skills in building more sophisticated and efficient applications. Step beyond the basics and dive deep into the world of microservices and RESTful APIs using the Spring Boot framework. This book provides the insights and advanced techniques you need to transform your applications from good to great. "Java Spring Boot: A Middle-Level Guide to Enhancing Microservices and RESTful APIs with Spring Boot" is more than just a programming book; it’s a comprehensive resource that will help you understand the subtleties and nuances of efficient application development. Whether you’re looking to specialize in microservices, enhance your API development skills, or simply take your Spring Boot knowledge to the next level, this book is your ideal companion. Developing RESTful APIs with Spring Boot is a preferred method for many software developers due to its robustness, straightforwardness, and the extensive functionality offered by the Spring ecosystem. Spring Boot enhances the capabilities of the Spring framework, facilitating the quick development and deployment of production-grade web services with minimal initial setup. Step up your development game and build better, faster, and more robust applications with Spring Boot by harnessing the advanced strategies and methodologies detailed in this essential guide.

Название: Грокаем конкурентность
Автор: Кирилл Бобров
Издательство: Питер
Год: 2025
Формат: pdf
Страниц: 273
Размер: 17,1 Мб
Язык: русский

Конкурентность позволяет эффективно выполнять компьютерные программы, разделяя их на задачи, которые можно запускать независимо. Такой подход помогает ускорить игровую графику, обучать большие модели искусственного интеллекта, быстро масштабировать веб-приложения, оптимизировать обработку больших данных и решать многие другие задачи. Работать с конкурентностью непросто, так что эта книга постепенно введет вас в курс дела, а помогут в этом интересные примеры, забавные иллюстрации и понятный код на Python. Вы изучите приемы, с помощью которых сможете программировать многоядерные и графические процессоры, а так же другие высокопроизводительные системы. Кирилл Бобров обходится без сложной математики, технического жаргона и тяжеловесных научных рассуждений, предпочитая простые и доступные объяснения.

Название: Kubernetes Observability in Action: Harnessing Innovative Observability using eBPF and Cilium
Автор: Gerardo López
Издательство: Independently published
Год: 2024
Страниц: 117
Язык: английский
Формат: epub
Размер: 10.1 MB

"Kubernetes Observability in Action" is an essential guide for professionals looking to enhance their understanding and capabilities in monitoring and troubleshooting Kubernetes environments. This book delves into the fundamental techniques and tools necessary for achieving deep observability in Kubernetes clusters, leveraging the powerful features of eBPF, Cilium, and Grafana. Take part in a thorough learning process that will help you understand not only the details of Kubernetes observability but also how to implement an initial observability platform. Use the combined power of K8s, Cilium, Grafana, Tempo, and Loki according to the guidance of a skilled professional to build a strong observability infrastructure. “Kubernetes Observability in Action” is not just a book; it’s an exploration into the realms of Kubernetes, eBPF, and the powerful synergy of Cilium and Grafana. In these pages, readers will embark on a journey that transcends traditional observability, diving into the intricate layers of containerized environments. We’ll unravel the potential of eBPF (Extended Berkeley Packet Filter) as a game-changing technology, unlocking unprecedented visibility into the inner workings of Kubernetes clusters.

Название: Coding & Programming User Manual - 23th Edition, September 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Страниц: 148
Язык: английский
Формат: pdf
Размер: 81.9 MB

Coding is everywhere. From your TV through to the International Space Station, you'll find millions of lines of code controlling and delivering the services that we take for granted. Behind all this code are the programmers who develop our digital world, using a multitude of different languages to weave the fabric of the Internet, operating systems, games and modern entertainment. We show you the fundamentals for Python, Linux, Raspberry Pi and C++, four of the most powerful languages in the world that are used by the likes of NASA, Microsoft, Apple and throughout the Internet. You will find ideas, concepts, tutorials, hints and projects that will take you from being a beginner to an advanced programmer able to form your own code. Your programming journey starts here...

Название: Artificial Intelligence in Healthcare: Emphasis on Diabetes, Hypertension, and Depression Management
Автор: Gourav Bathla, Sanoj Kumar, Harish Garg, Deepika Saini
Издательство: CRC Press
Серия: Intelligent Data-Driven Systems and Artificial Intelligence
Год: 2025
Страниц: 331
Язык: английский
Формат: pdf (true), epub
Размер: 10.5 MB

This book presents state-of-the-art research works for a better understanding of the advantages and limitations of AI techniques in the field of healthcare. It will further discuss Artificial Intelligence applications in depression, hypertension and diabetes management. The text also presents an Artificial Intelligence chatbot for depression, diabetes, and hypertension self-help. Many researchers have acknowledged Artificial Intelligence (AI) and Digital Twins (DT) as crucial technologies for the upcoming decade. They can optimise and integrate modern technologies like analytics, Artificial Intelligence and the Internet of Things (IoT). AI could revolutionize healthcare by improving efficiency, accuracy, and patient outcomes. Some of the notable healthcare applications of AI and DT in the domains of diagnostic imaging, such as radiology and pathology, could help radiologists and pathologists understand X-rays, MRIs, and CT images. AI could improve picture analysis in these sectors by discovering complicated patterns and abnormalities that challenge human visual perception. AI analyses large databases to speed up drug discovery. This technique finds new medication candidates, predicts their efficacy, and optimises their chemical structures. Personalised medicine uses AI to analyse patient data, including genetic information, to create treatment plans that match an individual’s qualities. This optimises medicine selection and dosing. Artificial Intelligence–powered virtual health assistants may answer questions and book appointments. The subtypes of AI known as Machine Learning (ML) and Deep Learning (DL) are both capable of finding creative solutions to challenges. Although ML research in precision cardiovascular care has expanded recently, Deep Learning is more recent, more sophisticated, and has different advantages and limits than ML. ML is useful for prediction by examining mechanisms and their correla­tions with specified variables using different training datasets, which may include different varieties and important data, such as multi-omics, social media, wearable technology, and standardized electronic health records. Both supervised and unsupervised learning are used for machine ML.

Название: Modern API Design: REST, GraphQL, and Beyond
Автор: Peter Johnson
Издательство: HiTeX Press
Год: 2024
Страниц: 343
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

"Modern API Design: REST, GraphQL, and Beyond" is an authoritative guide that offers a comprehensive exploration of APIs, emphasizing the intricacies of REST and GraphQL, the two dominant paradigms in the industry. This book caters to both novice and experienced developers, providing a deep dive into the essential principles of API design, including authentication, error handling, rate limiting, and security. Each concept is meticulously unpacked to ensure readers gain practical knowledge for implementing robust, scalable, and efficient APIs. Beyond the foundational elements, the book delves into advanced topics such as versioning strategies, testing, and documentation, as well as integration and management practices. It examines the role of API gateways, middleware, and lifecycle management, equipping readers with the tools and techniques necessary for effective API deployment and oversight. Case studies and real-world examples enrich the narrative, bridging theoretical knowledge and practical application. With a focus on best practices and industry standards, "Modern API Design: REST, GraphQL, and Beyond" serves as an indispensable resource for navigating the complex API landscape. Whether you're seeking to innovate or refine existing systems, this book is your guide to unlocking the full potential of APIs in today's digital world.

Название: Modern C++23 QuickStart Pro: Advanced programming including variadic templates, lambdas, async IO, multithreading and thread sync
Автор: Jarek Thalor
Издательство: GitforGits
Год: 2024
Страниц: 289
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Learn the latest features of C++23 with Modern C++ 23 QuickStart Pro, the perfect book for experienced developers who want to expand their knowledge and skills. This book takes a hands-on approach, providing rapid learning through real-world examples and scenarios that address complex programming challenges in C++. The book begins by demonstrating the power of variadic templates and how to use them for dynamic function signatures. After becoming familiar with fold expressions for argument handling, you will then explore std::tuple and std::variant for handling heterogeneous data. The book then covers advanced function morphing with parameter packs and shape-shifting lambdas, as well as dynamic programming techniques. It also teaches complex function overloading and high-level thread orchestration using futures, promises, and callables. Next, we'll go over some low-level IO operations, such as controlling IO streams, efficiently handling file descriptors, and directly manipulating files. You will then learn how to optimize memory management with shared, unique, and weak pointers, and how to engineer memory performance with custom allocators and cache-aware programming. You will learn advanced synchronization, including atomic operations, mutexes, locks, and thread pools, as well as lock-free data structures for peak performance. In addition, this book covers optimal integer and floating-point operations, arbitrary precision arithmetic, precise rounding with fixed-point arithmetic, and high-performance computation using math constant integration.

Название: No-Code Data Science: Mastering Advanced Analytics, Machine Learning, and Artificial Intelligence
Автор: David Patrishkoff, Robert E Hoyt
Издательство: Lulu.com
Год: October 16, 2023
Страниц: 872
Язык: английский
Формат: epub
Размер: 30.5 MB

No-Code Data Science is a revolutionary book that democratizes the application of predictive analytics for organizations of all sizes. This first-of-its-kind textbook book is designed to empower readers with the ability to leverage advanced analytics, Machine Learning, and AI without using a programming language, such as Python or R. It’s a comprehensive guide to No-Code Data Science (NCDS) that applies free, no-code, and open-source software with Orange visual programming software, JASP, and BlueSky Statistics. A no-shortcuts approach to ML and AI is applied to maximize the accuracy and application potential of predictive models. The NCDS approach is akin to constructing predictive models with pre-made LEGO bricks (visual programming) versus tediously molding shapes from clay (manual coding). A practical how-to approach to predictive modeling is offered while insisting on the rigor of our disciplined NCDS process. Hands-on data exercises are included in the first eleven chapters. QR code links to educational videos are included in most chapters. Data Science background is first explored, discussing basic definitions and data scientist skill sets. This is followed by chapters on data preparation, wrangling, and data visualization. Predictive analytics is covered in chapters on Machine Learning models and model evaluation. Both supervised and unsupervised learning are included in the discourse. Time series forecasting, survival analysis, and geolocation are covered in separate chapters. Artificial Intelligence (AI) is featured in chapters on image analysis and text mining.

Название: Advanced Techniques in Optimization for Machine Learning and Imaging
Автор: Alessandro Benfenati, Federica Porta, Tatiana Alessandra Bubba, Marco Viola
Издательство: Springer
Год: 2024
Страниц: 173
Язык: английский
Формат: pdf (true), epub
Размер: 55.2 MB

In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of Machine Learning and imaging. The present book is a collection of recent contributions in the field of optimization, either revisiting consolidated ideas to provide formal theoretical guarantees or providing comparative numerical studies for challenging inverse problems in imaging. The covered topics include non-smooth optimisation techniques for model-driven variational regularization, fixed-point continuation algorithms and their theoretical analysis for selection strategies of the regularization parameter for linear inverse problems in imaging, different perspectives on Support Vector Machines trained via Majorization-Minimization methods, generalization of Bayesian statistical frameworks to imaging problems, and creation of benchmark datasets for testing new methods and algorithms. In the past years, Support Vector Machines (SVMs) played a crucial role in the context of Machine Learning, for supervised classification and regression tasks. Even in the Deep Learning era, they can outperform other supervised methods and they are still a popular approach. The paper by A. Benfenati et al. investigates a novel approach by training SVMs via a squared hinge loss functional coupled with sparse-promoting regularization, adopting a Majorization-Minimization method. We perform numerical simulations to compare the performance of most commonly used Langevin Monte Carlo algorithms. The Langevin Monte Carlo (LMC) algorithm (possibly with Metropolis–Hastings adjustment), which is derived from the overdamped Langevin diffusion, has become a popular MCMC method for high-dimensional continuously differentiable distributions since it only requires access to a gradient oracle of the potential of the distribution, which can be computed easily using automatic differentiation softwares such as PyTorch, TensorFlow and JAX.

Название: Terraform Cookbook: Recipes for Codifying Infrastructure (Final Release)
Автор: Kerim Satirli, Taylor Dolezal
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 346
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Cloud services and SaaS software permeate every company's IT landscape, requiring a shift from manually provisioned services to a more structured approach, with codification at its core. Terraform provides tools to manage the lifecycle of your IT landscape across thousands of different cloud providers and SaaS platforms. By defining your infrastructure as code you can safely and predictably make changes, modularize crucial building blocks, and create reusable service components. Each recipe in this cookbook addresses a specific problem and prefaces the solution with detailed insights into the "how" and "why". If you're just starting with Terraform and codified infrastructure, this book will help you create a solid foundation, on which you can build for years to come. If you're an advanced user, this guide will help you reaffirm your knowledge and take it to the next level, as you challenge yourself with more complex infrastructure, spread across multiple providers. Terraform is a source-available tool created by HashiCorp that allows you to manage your infrastructure as code (IaC). It provides a simple and consistent way to define, provision, and manage resources across cloud platforms and on-premises environments. With Terraform, you can describe your infrastructure in a declarative language called the HashiCorp configuration language (HCL). This allows you to specify the desired state of your infrastructure rather than having to script the steps to get there. This book is for anyone responsible for creating, managing, or improving infrastructure. That includes DevOps engineers, site reliability engineers, infrastructure developers, system administrators, and even ambitious developers looking to broaden their skills.