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Название: Generative AI for Business: A Practical Guide to Harnessing AI and Delivering Real Business Value
Автор: Ayal Steinberg, Carlo Appugliese, Paul Hake, Simon Bisson
Издательство: O’Reilly Media, Inc.
Год: 2025-04-29
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Technologists and business leaders alike will explore the fundamental capabilities of Generative AI, high-impact use cases, key risks and challenges, technical integration considerations, and how to start building the necessary teams and culture for AI-enabled innovation. Whether you're just starting to explore this transformative technology or looking to scale its impact, you'll learn concrete strategies for harnessing the power of Generative AI to create measurable value for your business. Most applications of Generative AI, like ChatGPT, consist of more than just one LLM. An LLM can generate text, but if you ask it about images or audio the LLM doesn’t have the appropriate capabilities, so it needs to use tools just like we do when we do things. Tools allow the LLM to handle multiple input and output types, making it multimodal. If you ask ChatGPT to create an image, it will use an LLM to parse and summarize your input, building a prompt for another model, DALL-E, which handles the actual image generation. This is all done via function calling so that ChatGPT can create a seamless end user experience.

Название: Mastering Object-Oriented Programming: Essential Concepts and Techniques for Building Robust, Scalable Software Solutions
Автор: Virversity Online Courses
Издательство: eBookIt.com
Год: 2025
Страниц: 246
Язык: английский
Формат: pdf, epub (true)
Размер: 10.1 MB

Mastering Object-Oriented Programming is a comprehensive course designed to help you build a strong foundation in OOP concepts and practical skills. By understanding and applying core principles of object-oriented design, you'll be able to write cleaner, more efficient, and maintainable code for real-world applications. Learn To Design and Implement Robust Object-Oriented ProgramsGain a clear understanding of fundamental OOP concepts such as classes, objects, attributes, and methodsLearn key principles including encapsulation, inheritance, and polymorphism to create flexible and reusable codeMaster advanced topics like abstract classes, interfaces, and design patterns to improve software architectureDevelop skills in managing object lifecycles and handling exceptions gracefully within OOP contextsExplore industry best practices including SOLID principles, UML diagramming, and testing strategies.

Название: Automated Code Remediation at Scale: How to Refactor and Secure the Modern Software Supply Chain, 2nd Edition
Автор: Pat Johnson, Olga Kundzich, Jonathan Schneider
Издательство: O’Reilly Media, Inc.
Год: 2025-05-05
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

The software industrial revolution has arrived. Developers are building software faster than ever—assembled from third-party components, open source libraries, and AI-generated code. But what about maintaining and securing all of the code built by humans and AI? And how should companies address the corresponding acceleration of technical debt? Automated Code Remediation at Scale explains how organizations can automate software modernization and security for large, complex codebases. Packed with new content on the role AI tools now play in auto-remediation, this expanded second edition provides the guidance and real-world insights that will help you stay on top of software vulnerabilities and maintenance and tackle technical debt head-on.

Название: Machine Learning, Deep Learning and AI for Cybersecurity
Автор: Mark Stamp, Martin Jureček
Издательство: Springer
Год: 2025
Страниц: 636
Язык: английский
Формат: pdf
Размер: 26.8 MB

This book addresses a variety of problems that arise at the interface between AI techniques and challenging problems in cybersecurity. The book covers many of the issues that arise when applying AI and Deep Learning algorithms to inherently difficult problems in the security domain, such as malware detection and analysis, intrusion detection, spam detection, and various other subfields of cybersecurity. The book places particular attention on data driven approaches, where minimal expert domain knowledge is required. This book bridges some of the gaps that exist between Deep Learning/AI research and practical problems in cybersecurity. The proposed topics cover a wide range of Deep Learning and AI techniques, including novel frameworks and development tools enabling the audience to innovate with these cutting-edge research advancements in various security-related use cases. The book is timely since it is not common to find clearly elucidated research that applies the latest developments in AI to problems in cybersecurity.

Название: Quantum Algorithms: A Survey of Applications and End-to-end Complexities
Автор: Alexander M. Dalzell, Sam McArdle, Mario Berta
Издательство: Cambridge University Press
Год: 2025
Страниц: 436
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

The 1994 discovery of Shor's quantum algorithm for integer factorization―an important practical problem in the area of cryptography―demonstrated quantum computing's potential for real-world impact. Since then, researchers have worked intensively to expand the list of practical problems that quantum algorithms can solve effectively. This book surveys the fruits of this effort, covering proposed quantum algorithms for concrete problems in many application areas, including quantum chemistry, optimization, finance, and Machine Learning. For each quantum algorithm considered, the book clearly states the problem being solved and the full computational complexity of the procedure, making sure to account for the contribution from all the underlying primitive ingredients. Separately, the book provides a detailed, independent summary of the most common algorithmic primitives. It has a modular, encyclopedic format to facilitate navigation of the material and to provide a quick reference for designers of quantum algorithms and quantum computing researchers.

Название: Hands-On RAG for Production: Design, Develop, and Deploy Production-Ready RAG Applications (Early Release)
Автор: Ofer Mendelevitch, Forrest Bao
Издательство: O’Reilly Media, Inc.
Год: 2025-05-07
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Retrieval-augmented generation (RAG) is the go-to strategy for integrating large language models with your organization's unique knowledge. However, the market is full of RAG pipelines and components, making it hard to choose the right solution for your enterprise's needs. This book simplifies the process, offering a comprehensive road map to building, refining, and scaling production-grade RAG applications. Authors Ofer Mendelevitch and Forrest Bao guide you through every phase of development, from data ingestion, embeddings, and vector search to advanced techniques like agentic RAG, multimodal RAG, and GraphRAG. Engineers and architects will learn how to tackle the challenges they'll encounter when building RAG applications at enterprise scale: ensuring high accuracy with minimal hallucinations, maintaining low-latency performance, safeguarding data privacy, and providing transparent, explainable responses among them.

Название: Hands-On LLM Serving and Optimization: Hosting LLMs at Scale (Early Release)
Автор: Chi Wang, Peiheng Hu
Издательство: O’Reilly Media, Inc.
Год: 2025-05-05
Страниц: 124
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Large language models (LLMs) are rapidly becoming the backbone of AI-driven applications. Without proper optimization, however, LLMs can be expensive to run, slow to serve, and prone to performance bottlenecks. As the demand for real-time AI applications grows, along comes Hands-On Serving and Optimizing LLM Models, a comprehensive guide to the complexities of deploying and optimizing LLMs at scale. In this hands-on book, authors Chi Wang and Peiheng Hu take a real-world approach backed by practical examples and code, and assemble essential strategies for designing robust infrastructures that are equal to the demands of modern AI applications. Whether you're building high-performance AI systems or looking to enhance your knowledge of LLM optimization, this indispensable book will serve as a pillar of your success. Although different Machine Learning (ML) frameworks, such as TensorFlow and PyTorch, provide distinct APIs and libraries, the fundamental principles of model packaging and structure remain largely similar. In practice, additional optimizations are often applied to model files to enhance performance for model serving, particularly for large language models (LLMs).

Название: Deep Learning Recommender Systems
Автор: Zhe Wang, Chao Pu, Felice Wang
Издательство: Cambridge University Press
Год: 2025
Страниц: 314
Язык: английский
Формат: pdf
Размер: 24.6 MB

Recommender systems are ubiquitous in modern life and are one of the main monetization channels for Internet technology giants. This book helps graduate students, researchers and practitioners to get to grips with this cutting-edge field and build the thorough understanding and practical skills needed to progress in the area. It not only introduces the applications of Deep Learning and Generative AI for recommendation models, but also focuses on the industry architecture of the recommender systems. The authors include a detailed discussion of the implementation solutions used by companies such as YouTube, Alibaba, Airbnb and Netflix, as well as the related Machine Learning framework including model serving, model training, feature storage and data stream processing. Although the book will intersperse the ­introduction of basic Machine Learning knowledge, most of the content assumes that readers have some Machine Learning background.

Название: Distributed Time-Sensitive Systems
Автор: Tanupriya Choudhury, Rahul Kumar Singh, Ravi Tomar, S. Balamurugan
Издательство: Wiley-Scrivener
Год: 2025
Страниц: 375
Язык: английский
Формат: pdf (true), epub
Размер: 34.8 MB

The book provides invaluable insights into cutting-edge advancements across multiple sectors of Society 5.0, where contemporary concepts and interdisciplinary applications empower you to understand and engage with the transformative technologies shaping our future. Distributed Time-Sensitive Systems offers a comprehensive array of pioneering advancements across various sectors within Society 5.0, underpinned by cutting-edge technological innovations. This volume delivers an exhaustive selection of contemporary concepts, practical applications, and groundbreaking implementations that stand to enhance diverse facets of societal life. The chapters encompass detailed insights into fields such as image processing, natural language processing, computer vision, sentiment analysis, and voice and gesture recognition and feature interdisciplinary approaches spanning legal frameworks, medical systems, intelligent urban development, integrated cyber-physical systems infrastructure. Artificial Intelligence algorithms are used to automate jobs that were previously completed by humans. The main reason Artificial Intelligence (AI) is used in every aspect and industry is the intelligence it has provided through continuous learning from regularly trained models.

Название: Identity Security for Software Development: Best Practices That Every Developer Must Know
Автор: John Walsh, Uzi Ailon, Matt Barker
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 205
Язык: английский
Формат: PDF, True EPUB (Retail Copy)
Размер: 10.1 MB

Maintaining secrets, credentials, and machine identities in secure ways is an important, though often overlooked, aspect of secure software development. DevOps security often addresses vulnerabilities, but it neglects broader discussions like authentication, authorization, and access control, potentially leaving the door open for breaches. That's where an identity security strategy integrated in your code, infrastructure, and environments from day one can help. In this practical book, authors John Walsh, Uzi Ailon, and Matt Barker provide conceptual frameworks, technology overviews, and useful code snippets to bridge the gap between development, IT, and security to integrate robust identity security across apps, CI/CD pipelines, Kubernetes and cloud native, hybrid and multicloud, process automation, IoT, and more. This book is intended for developers, engineers, and dev-adjacent professionals who are involved in building, deploying, and securing software.