Sahu satej kumar (51 resultados)

Condición: Good. Good condition ex-library book with usual library markings and stickers.

Condición: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.

paperback. Condición: Very Good.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Paperback. Condición: New.

Condición: New.

Condición: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.

Paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: As New. Unread book in perfect condition.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: New. This is the first hands-on guide that takes you from a simple "Hello, LLM" to production-ready microservices, all within the JVM. You'll integrate hosted models such as OpenAI's GPT-4o, run alternatives with Ollama or Jlama, and embed them in Spring Boot or Quarkus apps for cloud or on-pre deployment.You'll learn how prompt-engineering patterns, Retrieval-Augmented Generation (RAG), vector stores such as Pinecone and Milvus, and agentic workflows come together to solve real business problems. Robust test suites, CI/CD pipelines, and security guardrails ensure your AI features reach production safely, while detailed observability playbooks help you catch hallucinations before your users do. You'll also explore DJL, the future of machine learning in Java. This book delivers runnable examples, clean architectural diagrams, and a GitHub repo you can clone on day one. Whether you're modernizing a legacy platform or launching a green-field service, you'll have a roadmap for adding state-of-the-art generative AI without abandoning the language-and ecosystem-you rely on. What You Will LearnEstablish generative AI and LLM foundationsIntegrate hosted or local models using Spring Boot, Quarkus, LangChain4j, Spring AI, OpenAI, Ollama, and JlamaCraft effective prompts and implement RAG with Pinecone or Milvus for context-rich answersBuild secure, observable, scalable AI microservices for cloud or on-prem deploymentTest outputs, add guardrails, and monitor performance of LLMs and applicationsExplore advanced patterns, such as agentic workflows, multimodal LLMs, and practical image-processing use cases Who This Book Is ForJava developers, architects, DevOps engineers, and technical leads who need to add AI features to new or existing enterprise systems. Data scientists and educators will also appreciate the code-first, Java-centric approach.…

Condición: As New. Unread book in perfect condition.

Condición: New. In English.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Condición: New. In English.

Condición: New. 1st ed. edition NO-PA16APR2015-KAP.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: New. Learn how to protect PHP applications from potential vulnerabilities and attacks. As cyberattacks and data breaches continue to rise, it's crucial for developers and organizations to prioritize security in their PHP applications. The book offers an all-encompassing guide to securing PHP applications, covering topics ranging from PHP core security to web security, framework security (with a focus on Laravel), security standards, and protocol security.After examining PHP core security and essential topics, such as input validation, output encoding, secure session management, and secure file handling, you'll move on to common security risks in PHP applications and provides practical examples to demonstrate effective security measures. From there, you'll delve into web security, addressing XSS, SQL injection, and CSRF, reviewing in-depth explanations and mitigation techniques.A significant portion of the book focuses on Laravel's built-in security features, guiding readers to avoid common pitfalls. Industry-standard security protocols like HTTP, OAuth, and JSON Web Tokens are explained with demonstrations for how to effectively use them to ensure integrity, confidentiality, and authenticity in web applications. Additionally, protocol security is discussed, including secure communication, file transfer protocols (SFTP), and email handling. Security in cloud and hybrid environments is also discussed.This book's comprehensive and inclusive approach spans a wide range of security topics related to PHP and ensures that no critical areas are overlooked. It goes beyond theoretical concepts by providing practical guidance and actionable steps. It includes code snippets, real-world examples, case studies, and hands-on exercises, enabling you to apply the knowledge gained in practical scenarios. Building Secure PHP Applications provides a holistic approach to security, empowering you to build robust and resilient PHP applications.What You Will LearnUnderstand industry-recognized security standards and compliance requirements for data protection regulations.Learn the intricacies of Laravel and how to leverage its security features.Integrate security practices throughout the development lifecycle, conducting security testing and reviews and adopting secure deployment and DevOps practices.Conduct forensic analysis and perform post-incident analysis for continuous improvement.Look to the future and discover emerging security threats and techniques to anticipate and mitigate potential security risks.Who This Book Is ForPrimarily written for developers, security professionals, and webmasters involved in PHP application development. Additionally, this book may be used as a reference for students studying web development, PHP programming or cybersecurity.…

Paperback. Condición: New. This is the first hands-on guide that takes you from a simple "Hello, LLM" to production-ready microservices, all within the JVM. You'll integrate hosted models such as OpenAI's GPT-4o, run alternatives with Ollama or Jlama, and embed them in Spring Boot or Quarkus apps for cloud or on-pre deployment.You'll learn how prompt-engineering patterns, Retrieval-Augmented Generation (RAG), vector stores such as Pinecone and Milvus, and agentic workflows come together to solve real business problems. Robust test suites, CI/CD pipelines, and security guardrails ensure your AI features reach production safely, while detailed observability playbooks help you catch hallucinations before your users do. You'll also explore DJL, the future of machine learning in Java. This book delivers runnable examples, clean architectural diagrams, and a GitHub repo you can clone on day one. Whether you're modernizing a legacy platform or launching a green-field service, you'll have a roadmap for adding state-of-the-art generative AI without abandoning the language-and ecosystem-you rely on. What You Will LearnEstablish generative AI and LLM foundationsIntegrate hosted or local models using Spring Boot, Quarkus, LangChain4j, Spring AI, OpenAI, Ollama, and JlamaCraft effective prompts and implement RAG with Pinecone or Milvus for context-rich answersBuild secure, observable, scalable AI microservices for cloud or on-prem deploymentTest outputs, add guardrails, and monitor performance of LLMs and applicationsExplore advanced patterns, such as agentic workflows, multimodal LLMs, and practical image-processing use cases Who This Book Is ForJava developers, architects, DevOps engineers, and technical leads who need to add AI features to new or existing enterprise systems. Data scientists and educators will also appreciate the code-first, Java-centric approach.…