Название: Multirate Signal Processing with Examples in Python
Автор: Gerald Schuller
Издательство: Springer
Год: 2026
Страниц: 151
Язык: английский
Формат: pdf (true), epub
Размер: 16.2 MB

This textbook provides a comprehensive understanding of multirate signal processing, focusing on practical applications and real-world examples implemented in Python. The book covers fundamental and advanced topics such as filter banks, sampling theory, and z-domain analysis, making it ideal for graduate-level courses and professionals. Through a combination of theoretical insights and Python-based examples, readers gain both the conceptual understanding and practical skills needed to apply multirate techniques in fields like audio coding, telecommunications, and Machine Learning. Ancillaries include homework problems, Python code examples, a Github repository with Colab Notebooks, and a chatbot for asking questions and finding answers quickly.

Название: Message- and Event-Driven Systems with CQRS and Event Sourcing: Web and Cloud Architecture (Early Release)
Автор: Alex Lawrence
Издательство: Addison-Wesley Professional/Pearson
Год: 2026
Страниц: 323
Язык: английский
Формат: epub
Размер: 15.1 MB

Learn How to Design and Build Scalable Systems Using Message-Driven Architecture, CQRS, and Event Sourcing. In today's fast-paced digital landscape, businesses must adapt rapidly to evolving demands. Message- and Event-Driven Systems with CQRS and Event Sourcing reveals how modern message-driven web and cloud architectures can fuel digital transformation, drive agility, and ensure robust scalability. This book bridges the gap between theory and practice, empowering architects and developers to build systems that thrive in the cloud era. Author Alex Lawrence demystifies a collection of widely discussed architectural patterns, clearly distinguishing between message-driven, event-driven, CQRS, and Event Sourcing approaches, and showing precisely when to apply each. By untangling concepts that are often confused, he provides both a strategic overview and practical guidance for designing each system component. Unlike most resources that focus on Java or C#, this book leverages Node.js, jаvascript, and TypeScript, making it uniquely relevant for today's web and cloud developers. Readers will discover how to isolate business capabilities, accelerate time-to-market, and future-proof their technology stack, enabling continuous evolution without sacrificing stability or performance.

Название: Mathematics Behind Neural Networks: 400 Illustrated Exercises from Algebra to Transformers
Автор: T Aadhya
Издательство: Independently published
Год: 2026
Страниц: 1294
Язык: английский
Формат: epub
Размер: 98.2 MB

Mathematics Behind Neural Networks: 400 Illustrated Exercises from Algebra to Transformers is a hands on workbook for readers who want to understand the mathematics inside modern neural networks, one computation at a time. If you have ever seen a neural network diagram and wanted to know what the numbers are actually doing, this book gives you the answer through worked exercises, clear notation, and structured practice. From scalars and vectors to matrix multiplication, activation functions, backpropagation, optimization, convolutional networks, recurrent networks, embeddings, and transformers, each chapter breaks the subject into concrete calculations you can perform by hand. This book is designed to help readers move beyond abstract explanations and build real mathematical fluency. The goal is not to guess the concept, but to calculate it clearly and correctly. This workbook takes that arithmetic seriously. Every one of the 400 problems in these pages asks you to compute something by hand—a forward pass, a gradient, an attention weight, a loss value. The problems are not puzzles or tricks. They are the exact computations that happen inside PyTorch and TensorFlow on every training step, made visible and tractable.

Название: Accelerating Deep Neural Networks
Автор: Ryoma Sato
Издательство: Cambridge University Press
Год: 2026
Страниц: 309
Язык: английский
Формат: pdf
Размер: 29.1 MB

Deep Learning models are powerful, but are often large, slow, and expensive to run. This book is a practical guide to accelerating and compressing neural networks using proven techniques such as quantization, pruning, distillation, and fast architectures. It explains how and why these methods work, fostering a comprehensive understanding. Written for engineers, researchers, and advanced students, the book combines clear theoretical insights with hands-on PyTorch implementations and numerical results. Readers will learn how to reduce inference time and memory usage, lower deployment costs, and select the right acceleration strategy for their task. Whether you're working with large language models, vision systems, or edge devices, this book gives you the tools and intuition needed to build faster, leaner AI systems, without sacrificing performance. The target readers of this book are Machine Learning engineers, researchers, and students aspiring to enter these fields. Although basic concepts are explained as clearly as possible, a basic understanding of deep neural networks and undergraduate-level linear algebra and calculus is recommended. For those uncertain about their foundational knowledge of deep neural networks, it may be helpful to review tutorials for PyTorch or TensorFlow. All programs were developed using Python 3.11.9 and PyTorch 2.3.1.

Название: Алгоритмы: теория и практическое применение
Автор: Стивенс Род
Издательство: М.: Эксмо
Год: 2016
Cтраниц: 544
Формат: pdf
Размер: 78 мб
Язык: русский

Алгоритмы – это рецепты, которые делают возможным эффективное программирование. Их изучение позволяет усвоить общие подходы к решению задач и накапливать полезные методики для их решения. В этой книге представлено множество классических алгоритмов, вы узнаете, где они применяются и как их анализировать, чтобы понять их поведение. Эта книга может быть полезной не только в вашей текущей профессиональной деятельности, но и поможет вам получить новую работу.

Название: Large Language Models: The Hard Parts: Open Source AI Solutions for Common Pitfalls (Final Release)
Автор: Thársis T.P. Souza, Jonathan K. Regenstein, Jr
Издательство: O’Reilly Media, Inc.
Год: 2026
Страниц: 341
Язык: английский
Формат: True PDF, True EPUB
Размер: 31.0 MB

Large language models (LLMs) have transformed natural language processing, but deploying them in applications introduces numerous technical challenges. Large Language Models: The Hard Parts offers a clear, practical examination of the limitations developers and AI engineers face when building LLM-based applications. With a focus on implementation pitfalls (not just capabilities), this book provides actionable strategies supported by reproducible Python code and open source tools. Readers will learn how to navigate key obstacles in application evaluation, input management, testing, and safety. Designed for builders and technical product leads, this guide emphasizes practical solutions to real-world problems and promotes a grounded understanding of LLM constraints and trade-offs. In recent years, LLMs have emerged as a transformative force in technology. We wrote this book because we’re optimistic about the power and possibilities of LLMs but realistic about how hard it is to deploy them successfully, widely, and reliably. This book focuses on bringing awareness to key LLM challenges and harnessing open source solutions to overcome them. It offers a critical perspective on implementation, backed by practical and reproducible Python examples.

Название: AI-Ready Data Blueprints: From Raw Data to AI-Driven Innovation (Final Release)
Автор: Navnit Shukla, Kien Pham, Srikanth Sopirala, Harsha Tadiparthi
Издательство: O’Reilly Media, Inc.
Год: 2026
Страниц: 293
Язык: английский
Формат: True PDF, True EPUB
Размер: 16.2 MB

Companies innovating with Generative AI understand that having the right data foundation is critical for success and profitability. To best position themselves for long-term success, organizations must prioritize investments in data and AI governance. AI-Ready Data Blueprints is your map to connecting data strategy, GenAI, and ethical practices to build and scale truly effective solutions. Taking a comprehensive, cloud-agnostic approach focused on real-world business challenges, seasoned data and AI experts Navnit Shukla, Kien Pham, Srikanth Sopirala, and Harsha Tadiparthi share actionable insights to guide you in designing and implementing effective data-centric GenAI systems. Whether you're new to GenAI or are already focusing on optimizing it for accuracy, speed, or both, the principles shared in this book will empower you to excel in all your AI endeavors. This book follows the journey your data takes—from raw, messy, and scattered to AI-ready, governed, and production-grade. We start by laying out why generative AI demands a fundamentally different approach to data than traditional analytics or Machine Learning. Blueprints, architecture diagrams, and sample code are available via the book’s companion website and GitHub repository.

Название: Mastering Claude Code: Real-World Projects, Prompts, and Workflows for AI-Powered Development
Автор: Kilian Voss
Издательство: Independently published
Год: October 19, 2025
Страниц: 534
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Unleash the power of Claude Code, Anthropic’s cutting-edge AI coding assistant. Mastering Claude Code shows you how to integrate Claude into your workflow with practical, hands-on projects. You’ll learn to write effective prompt engineering strategies and use Claude’s code-writing, debugging, and refactoring capabilities to supercharge development. Whether you’re a solo developer or leading a tech team, this book transforms AI hype into real coding productivity. Built around real-world projects, this guide walks you through complete examples – from designing and coding a REST API to automating infrastructure and even building your own multi-agent development assistant. Each project is explained step-by-step, with tested code examples and clear explanations. You’ll discover how Claude thinks about code, how to manage large codebases and long contexts, and how to refine Claude’s output for accuracy, performance, and cost. The book also covers integration with popular tools (VS Code, Zed, Git, CI/CD), enterprise concerns (security, governance, compliance), and performance tuning so you can use Claude in professional environments. This book is written for developers who build things, not just those who talk about them.

Название: Artificial Intelligence in Digital Image Processing: Theories, Methods, and Applications
Автор: Hang Chen, Zhengjun Liu
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2026
Страниц: 281
Язык: английский
Формат: pdf (true), epub
Размер: 93.6 MB

This book is a focused, practice-driven resource organized around 10 key thematic sections, blending foundational AI knowledge with cutting-edge digital image processing applications—ideal for bridging theory and real-world use. It avoids generic coverage, instead diving into specialized, high-demand topics like Deep Learning fundamentals, deepfake technology, adversarial attacks in Computer Vision, adaptive cryptography, and Generative AI-driven SAR-to-optical image translation. As a postgraduate handbook, it aligns perfectly with courses such as “AI Image Processing,” “Advanced Signal Processing,” and “Optical Information Security,” helping students grasp core concepts and build practical skills. We hope this book serves as a valuable resource: for students, a textbook to build from AI fundamentals to specialized applications; for researchers, a reference to explore frontiers like deepfake detection, adaptive cryptography, and generative image translation; and for practitioners, a guide to translating academic innovation into solutions for remote sensing, healthcare, and image security.

Название: Vibe Engineering: Best practices, mistakes, and tradeoffs (MEAP v4)
Автор: Tomasz Lelek, Artur Skowroński
Издательство: Manning Publications
Год: 2026
Страниц: 265
Язык: английский
Формат: pdf (true), epub
Размер: 13.2 MB

Master vibe engineering—an end-to-end process to navigate the costs, benefits, and tradeoffs of AI-augmented development. Generating code with AI can feel effortless, but it’s only one part of software engineering. A production-grade development pipeline includes testing, validation, refactoring, optimization, and deployment. This book shows you how to go from AI-assisted coding to a AI-infused full-spectrum process author Tomasz Lelek and Artur Skowronski call vibe engineering. Vibe Engineering lays out a provider-agnostic framework that’s focused on small, easily comprehensible code increments. Fully illustrated with real-world scenarios, you’ll explore industry use cases, from modernizing a legacy codebase to implementing Continuous AI Development. You’ll learn how to keep the benefits of speed and efficiency AI-assisted coding can deliver without sacrificing accuracy, maintainability, and trust. For software engineers, tech leads, and engineering managers. To get the most out of this book, you should have a basic familiarity with Java (and optionally Python) and feel comfortable using a modern IDE such as IntelliJ IDEA or Visual Studio Code.