Название: Solid Router: The Complete Guide
Автор: Sinan Polat
Издательство: Leanpub
Год: 2025
Страниц: 122
Язык: английский
Формат: pdf (true), mobi, epub
Размер: 10.1 MB

Master Solid Router with this focused, hands-on guide. Learn the fundamentals of route configuration, navigation, and parameters, then dive into advanced topics like data loading, async handling, prefetching, and performance tuning. Whether building SolidJS SPAs or SolidStart apps, this book equips you with the practical skills to ship fast, scalable, production-ready experiences. Every modern web application needs navigation. Whether it is a small single-page app or a full-fledged platform with nested layouts, dynamic segments, and preloaded data, routing is the connective tissue that ties the user experience together. In the SolidJS world, that job is handled by Solid Router. This book provides a focused and practical guide to Solid Router. If you are already comfortable with SolidJS basics and want to dive straight into building real applications with routing, this book is for you. It is lean, focused, and ready to get you up and running. This book is not an introduction to SolidJS itself. It assumes familiarity with the following: • SolidJS fundamentals: signals, stores, components, and JSX usage; • TypeScript: while not strictly required, examples and best practices in this book use TypeScript for type safety and clarity; • Basic web development concepts: including HTML, CSS, and jаvascript modules.

Название: Architected Intelligence: Principles for Building AI-First Organizations and Technologies
Автор: Jacob Miller, Jeremy Mumford
Издательство: Wiley
Год: 2026
Страниц: 411
Язык: английский
Формат: True PDF, True/Retail EPUB
Размер: 18.7 MB

Most AI initiatives fail. Transform AI potential into organizational results through the Architected Intelligence framework. The gap between a dazzling "cool demo" and a reliable, production-grade system is a chasm that is swallowing teams and entire organizations. Architected Intelligence is your definitive map at both the organizational and tactical levels to cross this divide. Drawing on their experience building the world's largest ecommerce accelerator, authors Jacob Miller and Jeremy Mumford deliver actionable guidance for organizations struggling to turn proofs of concept into production systems. Whether you are competing in the age of AI or looking to establish technology leadership in your sector, this book organizes AI success around a unified framework of five core components: - Design AI Systems to Deliver Impactful Output; - Power AI with High-Quality Input Data; - Engineer, Optimize, and Integrate AI Models; - Create Trust through Observability; - Scale Transformation through AI Enablement.

Название: Basic Computer Coding: Lua
Автор: Katya Podkovyroff
Издательство: 3G E-learning LLC
Год: 2024
Страниц: 250
Язык: английский
Формат: pdf (true)
Размер: 11.3 MB

Lua is a versatile and powerful scripting language that has gained significant popularity among developers and programmers. Designed for easy integration and extensibility, Lua provides a range of features that make it an ideal choice for a variety of applications. It is implemented in ANSI C, a subset of the C programming language that is very portable, which means it can run on many systems and many devices where most other scripting languages would not be able to run. One of the key strengths of Lua lies in its simplicity. Despite being a fully functional programming language, Lua boasts a clean and straightforward syntax that is easy to understand and learn, even for beginners. This makes it an excellent choice for individuals who are new to coding or scripting. Lua is often praised for its flexibility, allowing developers to extend and customize applications according to their specific needs. It provides a mechanism of tables, which implements concepts like records, arrays, and recursive data types. Furthermore, Lua incorporates object-oriented facilities, such as dynamic dispatching for methods. The language also offers a unique feature called fallbacks.

Название: BIM Geometry with Julia Plasm―Functional Language for CAD Programming: Volume 1: Mathematics and Software Engineering
Автор: Alberto Paoluzzi, Giorgio Scorzelli
Издательство: Springer
Год: 2026
Страниц: 317
Язык: английский
Формат: pdf (true)
Размер: 27.4 MB

This book provides computational methods, tools, algorithms, code scriptlets, and examples for symbolically generating simple and very complex geometric shapes as solid models and structures for Building Information Modeling (BIM) environments. The book introduces the Programming Language for Symbolic/Solid Modeling (Plasm), a concise symbolic design language for the construction industry. It explains how to utilize the recent adaptation to the MIT-originated language Julia, regarded as the premier modern language for scientific computing. In this context, the design is stored as a solid model and can be utilized by other Julia packages (e.g., for mechanical, thermal, simulation, etc.). In the last ten years, the scientific programming field has witnessed the emergence of the Julia language, which is as fast as C and C++ but as user-friendly as Python and Matlab—porting PLaSM to Julia and giving the community a multidimensional geometry engine in the form of the Plasm.jl package was a natural step and much easier than we had anticipated. We hope it will provide the geometric tools that Julia currently lacks and more.

Название: Federated Learning: From Theory to Practice
Автор: Alexander Jung
Издательство: Springer
Год: 2026
Страниц: 221
Язык: английский
Формат: pdf (true), epub
Размер: 27.3 MB

How can we train powerful Machine Learning models together—across smartphones, hospitals, or financial institutions—without ever sharing raw data? This book delivers a compelling answer through the lens of Federated Learning (FL), a cutting-edge paradigm for decentralized, privacy-preserving machine learning. Designed for students, engineers, and researchers, this book offers a principled yet practical roadmap to building secure, scalable, and trustworthy FL systems from scratch. At the heart of this book is a unifying framework that treats FL as a network-regularized optimization problem. This elegant formulation allows readers to seamlessly address personalization, robustness, and fairness—challenges often tackled in isolation. You’ll learn how to structure FL networks based on task similarity, leverage graph-based methods and apply distributed optimization techniques to implement FL systems. Detailed pseudocode, intuitive explanations, and implementation-ready algorithms ensure you not only understand the theory but can apply it in real-world systems.

Название: Generative AI Ethics, Privacy, and Security: A guide to generative AI, its ethical considerations, privacy measures, security strategies, and approaches
Автор: Wrick Talukdar, Anjanava Biswas
Издательство: BPB Publications
Год: 2025
Страниц: 284
Язык: английский
Формат: pdf, epub (true)
Размер: 11.3 MB

Generative AI is transforming industries globally, with the majority of organizations using Generative AI in at least one business function. From the fundamental evolution of transformer models to the complex ethical questions they raise, this book equips readers with the knowledge to navigate AI with confidence. This book begins by introducing foundational concepts of Generative AI and transformer model evolution, along with architectures, including GANs and autoencoders. It explores ethical frameworks and societal impacts, examines privacy challenges in data usage and generated content, and addresses security threats with mitigation strategies. Readers will learn responsible development and governance practices, navigate the legal and regulatory landscape, and learn how to educate users about AI capabilities and limitations. The book concludes with real-world case studies, best practices for deployment, and future directions for ethical innovation. Upon completing this book, readers will possess the knowledge and skills to lead generative AI initiatives, balancing innovation with ethical responsibility. This book is designed for ML engineers, architects, developers, business leaders, and AI strategists who need to understand both the technical and ethical dimensions of Generative AI.

Название: Applied Mathematics for Healthcare Intelligent Systems: Data Representation, Smart Healthcare, Deep Learning and Medical Imaging
Автор: Monika Sethi, Shivani Sood, Saravjeet Singh, Arfat Ahmad Khan
Издательство: De Gruyter
Год: 2026
Страниц: 329
Язык: английский
Формат: pdf (true), epub
Размер: 51.1 MB

This book offers a comprehensive and interdisciplinary perspective on healthcare intelligent systems, highlighting the growing role of applied mathematics, data-driven methodologies, and Artificial Intelligence in modern healthcare. The book brings together scholarly contributions that explore how intelligent models, data representations, and computational techniques are applied to healthcare diagnostics, medical imaging, and clinical decision-support systems. The chapters cover a wide range of topics, including medical imaging modalities, data handling and representation, Deep Learning techniques, explainable and trustworthy Artificial Intelligence, generative models, three-dimensional reconstruction, performance evaluation metrics, ethical considerations, and emerging trends in healthcare technologies. Through practical insights and real-world case studies, the volume illustrates how intelligent systems support disease detection, diagnosis, and personalized treatment planning. Designed for researchers, graduate students, and professionals in healthcare technology, Computer Science, and biomedical engineering, this book serves as a valuable reference on intelligent healthcare solutions.

Название: Neurosymbolic AI: Foundations and Applications
Автор: Alvaro Velasquez, Houbing Herbert Song, Pradeep Ravikumar, S. Shankar Sastry
Издательство: Wiley-IEEE Press
Год: 2026
Страниц: 495
Язык: английский
Формат: pdf (true)
Размер: 11.5 MB

An up-to-date and expert discussion of neuro-symbolic Artificial Intelligence development. In Neuro-symbolic AI: Foundations and Applications, a team of distinguished researchers delivers a comprehensive overview of the emerging field of neuro-symbolic Artificial Intelligence. Expert contributors explain the integration of symbolic representations with neural networks, demonstrating state-of-the-art practices in the field. The book fosters collaboration amongst diverse disciplines and promotes a deeper understanding of the challenges posed by Deep Learning, including generalizability, explainability, and robustness. Perfect for researchers and professionals in Artificial Intelligence involved industries, including autonomous driving, military, healthcare, and finance, Neuro-symbolic AI: Foundations and Applications will also benefit students of Computer Science, software engineering, Data Science, and Machine Learning.

Название: Applied Machine Learning on Sensing Technologies
Автор: Atiqur Rahman Ahad, Anton Nijholt, Abdus Samad Kamal
Издательство: CRC Press
Год: 2026
Страниц: 302
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

This book explores applied Machine Learning and Deep Learning in the field of sensing, vision and sensor-based applications. It includes a series of methodologies, exploration of new applications, presentations on relevant datasets, challenging applications, guidelines, ideas and future scopes. Edited by leading experts in these arenas, the book will be of great interest to academic researchers, graduate students and industry professionals in the fields of Machine Learning, Deep Learning, AI, sensing, computer vision and sensors. Traditional ML models are employed with the available information to recommend a crop for the selected land and provide decent accuracy. These models include unsupervised models like K-Means and other clustering algorithms as well as supervised models like Naive Bayes (NB), Support Vector Machines (SVM), and Neural Networks (NN). Deep Learning models differ from the previously described ML models in the way that they tune the model parameters using automatic feature learning techniques.

Название: Practical AI Security: A Hands-on Guide to Attacking, Defending, and Securing Modern AI Systems
Автор: Harriet Farlow
Издательство: No Starch Press
Год: 2026
Страниц: 392
Язык: английский
Формат: epub
Размер: 21.0 MB

Break AI Systems. Then Secure Them. If you’re a security practitioner learning to operate in AI environments, or an ML engineer who needs to understand what adversaries actually do, Practical AI Security gives you the technical foundation the field demands. Built from first principles, this book takes you from how models fail to how they’re exploited to how they’re defended and audited. Every technique includes clear explanations and real-world examples, and you can run the attacks and defenses yourself with over 30 hands-on Python demos. While I assume you have some basic understanding of math, Python coding, and security principles, I don’t expect you to be an expert in any of these disciplines. My goal is to give you broad, foundational knowledge across the field so that you can decide which areas you want to go deeper into.