Wydawnictwo O'Reilly Media - ebooki
Tytuły książek wydawnictwa: O'Reilly Media
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Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI expe-
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Generative AI is revolutionizing industries, and Kubernetes has fast become the backbone for deploying and managing these resource-intensive workloads. This book serves as a practical, hands-on guide for MLOps engineers, software developers, Kubernetes administrators, and AI professionals ready to combine AI innovation with the power of cloud nativ
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Successfully delivering AI projects requires more than technical expertise—it demands a new kind of project management. Managing AI Projects is your practical guide to leading artificial intelligence initiatives from idea to production. Written by seasoned experts Malini Jain Runtasewee and Adrián González Sánchez, this book
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(95,40 zł najniższa cena z 30 dni)
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Generative AI has revolutionized how organizations tackle problems, accelerating the journey from concept to prototype to solution. As the models become increasingly capable, we have witnessed a new design pattern emerge: AI agents. By combining tools, knowledge, memory, and learning with advanced foundation models, we can now sequence multiple mod
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With the GenAI boom showing no sign of letup, the demand for AI skills will only increase with time and innovation. Microsoft Azure leads the pack with services for developing and deploying AI solutions, so professionals looking to break into this field should consider pursuing certification as an Azure AI Engineer Associate. Azure's AI-102 exam is
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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 build
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Large language models (LLMs) are the reasoning engines of modern AI. Today, a major inflection point has arrived: as the world races to deploy AI at scale, model inference has moved to the center of the stack. Welcome to the inference era. Without proper optimization, however, LLMs can be expensive and slow to serve. Hands-On LLM Serving and Optim
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With the introduction of the EU AI Act, companies employing AI systems face a new set of comprehensive and stringent regulations. Dr. Larysa Visengeriyeva offers a much-needed guide for navigating these unfamiliar regulatory waters to help you meet compliance challenges with confidence. From explaining the legislative framework to sharing strategie
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Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, ma
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If you're looking to build production-ready AI applications that can reason and retrieve external data for context-awareness, you'll need to master--;a popular development framework and platform for building, running, and managing agentic applications. LangChain is used by several leading companies, including Zapier, Replit, Databricks, and many mo
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With the rise of autonomous agents, the question is no longer "How do we build agents?" but rather, "How do we manage an entire ecosystem of them?" This book explores the next frontier of this technology, where interconnected agents collaborate, transact, and fulfill tasks autonomously. Building on established concepts like API service mesh and dat
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AI is transforming software development, shifting programmers from writing code to collaborating with AI in an intent-driven workflow. Vibe coding—a prompt-first, exploratory approach where you describe what you want in natural language and let a large language model fill in the blanks—represents a radical shift in the developer's role
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Large language models (LLMs) have proven themselves to be powerful tools for solving a wide range of tasks, and enterprises have taken note. But transitioning from demos and prototypes to full-fledged applications can be difficult. This book helps close that gap, providing the tools, techniques, and playbooks that practitioners need to build useful
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AI is only as capable as the context it's given, and context is a data engineering problem before it's a model problem. As multimodal AI systems and applications become increasingly sophisticated and data-hungry, the infrastructure that produces and governs that context has to evolve to keep pace. Data Engineering for Multimodal AI is one of the fi
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Video generation is rapidly becoming a key area in generative AI, combining spatial, temporal, and multimodal reasoning to produce moving images that are both coherent and creative. For many practitioners, however, understanding how these models function and implementing them remains a significant challenge. Video Generation with AI offers a straig
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La IA generativa ha revolucionado la forma en que las organizaciones abordan los problemas, acelerando el proceso desde el concepto hasta el prototipo y la solución. A medida que los modelos se vuelven cada vez más capaces, hemos visto surgir un nuevo patrón de diseńo: los agentes de IA. Al combinar herramientas, conocimiento, memoria y aprendizaje
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As generative AI becomes central to modern data and machine learning workflows, earning the Databricks Certified Generative AI Engineer Associate certification signals both credibility and technical fluency. This study guide prepares you for this sought-after certification with comprehensive coverage of core GenAI and LLM concepts, practical data m
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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
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Learning AutoML is your practical guide to applying automated machine learning in real-world environments. Whether you're a data scientist, ML engineer, or AI researcher, this book helps you move beyond experimentation to build and deploy high-performing models with less manual tuning and more automation. Using AutoGluon as a primary toolkit, you'l
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The vast potential of AI technology remains untapped in areas like audio, video, and complex data analysis. In fact, many of today's professionals find it challenging to apply AI innovations across these diverse domains due to a lack of guidance and practical implementations.This comprehensive guide, tailored especially for intermediate to advanced
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Agentic AI promises new levels of automation and adaptability, but it also introduces complexity in governance, interoperability, and scale. To navigate these challenges, leaders need a clear adoption playbook. This guide gives them a practical framework for understanding what agentic AI can—and can't—do, identifying the right opportuni
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Questo lavoro č stato tradotto utilizzando l'AI. Siamo lieti di ricevere il tuo feedback e i tuoi commenti: translation-feedback@oreilly.com I recenti progressi nell'intelligenza artificiale non solo hanno fatto crescere la domanda di prodotti AI, ma hanno anche reso piů facile per chiunque voglia creare prodotti AI. L'approccio &quo
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In today's AI landscape, success depends not just on prompting large language models but on orchestrating them into intelligent systems that are scalable, compliant, and cost-effective. GenAI on Google Cloud is your hands-on guide to bridging that gap. Whether you're an ML engineer or an enterprise leader, this book offers a practical game plan for
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Los recientes avances en IA no sólo han aumentado la demanda de productos de IA, sino que también han reducido las barreras de entrada para quienes quieren crear productos de IA. El enfoque del modelo como servicio ha transformado la IA de una disciplina esotérica en una potente herramienta de desarrollo que cualquiera puede ut
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Elevate your AI system performance capabilities with this definitive guide to maximizing efficiency across every layer of your AI infrastructure. In today's era of ever-growing generative models, AI Systems Performance Engineering provides engineers, researchers, and developers with a hands-on set of actionable optimization strategies. Learn to co-
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(197,40 zł najniższa cena z 30 dni)
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Get up to speed on a new unified approach to building machine learning (ML) systems with a feature store. Using this practical book, data scientists and ML engineers will learn in detail how to develop and operate batch, real-time, and agentic ML systems. Author Jim Dowling introduces fundamental principles and practices for developing, testing, an
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In the era of big data and even bigger machine learning models powering the current generative AI revolution, the environmental footprint of these developments can no longer be ignored. This much-needed guide confronts the challenge head-on, offering a groundbreaking exploration into making deep learning (DL) both efficient and accessible. Author R
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Generative AI enables powerful new capabilities, but they come with some serious limitations that you'll have to tackle to ship a reliable application or agent. Luckily, experts in the field have compiled a library of 32 tried-and-true design patterns to address the challenges you're likely to encounter when building applications using LLMs, such a
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AI coding assistants are helping teams create software faster than ever. But to turn that speed into real innovation, organizations must go beyond writing code and deliver software quickly, securely, and reliably. While AI-assisted coding is now mainstream, what happens after the code is written is still catching up. AI-Native Software Delivery is
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Feeling overwhelmed by the volume of data in your research? Sifting through massive amounts of data to find useful insights is becoming increasingly difficult in drug discovery, genetics, and healthcare. Enter the era of generative AI with LangChain, whose groundbreaking tools are changing the way life scientists and researchers operate. In this g
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Here's the thing about large language models: they don't play by the old rules. Traditional MLOps completely falls apart when you're dealing with GenAI. The model hallucinates, security assumptions crumble, monitoring breaks, and agents can't operate. Suddenly you're in uncharted territory. That's exactly why LLMOps has emerged as its own disciplin
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Drawing from her experience at Google and Meta, Dr. Marily Nika delivers the definitive guide for product managers building AI and GenAI powered products. Packed with smart strategies, actionable tools, and real-world examples, this book breaks down the complex world of AI agents and generative AI products into a playbook for driving innovation to
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Using machine learning for products, services, and critical business processes is quite different from using ML in an academic or research setting—especially for recent ML graduates and those moving from research to a commercial environment. Whether you currently work to create products and services that use ML, or would like to in the future
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Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and gene
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Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, da
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Your training data has as much to do with the success of your data project as the algorithms themselves because most failures in AI systems relate to training data. But while training data is the foundation for successful AI and machine learning, there are few comprehensive resources to help you ace the process. In this hands-on guide, author Anth
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Decision intelligence (DI) has been widely named as a top technology trend for several years, and Gartner reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or d
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Remove your doubts about AI and explore how this technology can be future-proofed using blockchain's smart contracts and tamper-evident ledgers. With this practical book, system architects, software engineers, and systems solution specialists will learn how enterprise blockchain provides permanent provenance of AI, removes the mystery, and allows y
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Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine learning, developers can capture human intuition and deploy it to any target--from ultra-low pow
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Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early
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Whether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, product managers, and business owners how to run and establish ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitor
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AI is poised to transform every aspect of healthcare, including the way we manage personal health, from customer experience and clinical care to healthcare cost reductions. This practical book is one of the first to describe present and future use cases where AI can help solve pernicious healthcare problems.Kerrie Holley and Siupo Becker provide gu
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With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in
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More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact.This book introduces the key
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The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable a
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Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that
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AI may be the greatest opportunity of our time, with the potential to add nearly $16 trillion to the global economy over the next decade. But so far, adoption has been much slower than anticipated, or so headlines may lead you to believe. With this practical guide, business leaders will discover where they are in their AI journey and learn the step
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Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers—including experienced practitioners and novices al
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Much in the same way that software transformed business in the past two decades, AI is set to redefine organizations and entire industries. Just as every company is a software company today, every company will soon be an AI company.This practical guide explains how business and technical leaders can embrace this new breed of organization. Based on
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With this practical book, architects, CTOs, and CIOs will learn a set of patterns for the practice of architecture, including analysis, documentation, and communication. Author Eben Hewitt shows you how to create holistic and thoughtful technology plans, communicate them clearly, lead people toward the vision, and become a great architect or Chief
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If youâ??re an executive, manager, or anyone interested in leveraging AI within your organization, this is your guide. Youâ??ll understand exactly what AI is, learn how to identify AI opportunities, and develop and execute a successful AI vision and strategy. Alex Castrounis,founder and CEO of Why of AI, Northwestern Universit
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