Visar resultat för..."O'Reilly Media"

Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of tools and analytical systems, including relational databases, NoSQL datastores, plus data warehouses and data lakes. What are the right choices for your application? How do you make sense of all these buzzwords?In this second edition, authors Martin Kleppmann and Chris Riccomini build on the foundation laid in the acclaimed first edition, integrating new technologies and emerging trends. You'll be guided through the maze of decisions and trade-offs involved in building a modern data system, from choosing the right tools like Spark and Flink to understanding the intricacies of data laws like the GDPR.Peer under the hood of the systems you already use, and learn to use them more effectivelyMake informed decisions by identifying the strengths and weaknesses of different toolsNavigate the trade-offs around consistency, scalability, fault tolerance, and complexityUnderstand the distributed systems research upon which modern databases are builtPeek behind the scenes of major online services, and learn from their architectures

Do you want to build web pages but have no prior experience? This friendly guide is the perfect place to start. You'll begin at square one, learning how the web and web pages work, and then steadily build from there. By the end of the book, you'll have the skills to create a simple site with multicolumn pages that adapt for mobile devices. Each chapter provides exercises to help you learn various techniques and short quizzes to make sure you understand key concepts. This thoroughly revised edition is ideal for students and professionals of all backgrounds and skill levels. It is simple and clear enough for beginners, yet thorough enough to be a useful reference for experienced developers keeping their skills up to date.

When every safeguard is in place and your distributed system still fails, a simplistic, narrow view of system resilience is no longer enough. Modern software architectures, amplified by unpredictable AI components, demand a different approach to preventing catastrophic downtime.In Building Resilient Distributed Systems, author Sam Newman offers a modern blueprint for surviving real-world system failures. The book combines wisdom from safety-critical systems with proven patterns, giving you a practical pathway to building more resilient AI-powered software that adapts and endures. Whether you're refining an existing system, creating new distributed systems, or simply striving to grasp the essence of resilience, you'll learn how to design systems that fail gracefully instead of collapsing.By the end, you'll be able to:Grasp the true essence of resilience by integrating safety and human factorsMake use of patterns that improve system stabilityTranslate resilience theories into practical actionsUnderstand critical architectural trade-offs to ensure systems degrade gracefullyLearn how distributed systems are fundamentally sociotechnical systems that sit at the intersection of people and technologyEmbrace the necessary cultural and behavioral shifts to support a resilient system

Python is an excellent way to get started in programming, and this clear, concise guide walks you through Python a step at a time-beginning with basic programming concepts before moving on to functions, data structures, and object-oriented design. This revised third edition reflects the growing role of large language models (LLMs) in programming and includes exercises on effective LLM prompts, testing code, and debugging skills.With this popular hands-on guide at your side, you'll get:A grounding in the syntax and semantics of the Python languageA clear definition of each programming concept, with emphasis on clear vocabularyHow to work with variables, statements, functions, and data structures in a logical progressionTechniques for reading and writing files and databasesA solid understanding of objects, methods, and object-oriented programmingDebugging strategies for syntax, runtime, and semantic errorsAn introduction to recursion, interface design, data structures, and basic algorithmsHow to use LLMs-including effective prompts, testing code, and debuggingAnd more

Managing people is difficult wherever you work. But in the tech industry, where management is also a technical discipline, the learning curve can be brutal-especially when there are few tools, texts, and frameworks to help you. In this practical guide, author Camille Fournier (tech lead turned CTO) takes you through each stage in the journey from engineer to technical manager. From mentoring interns to working with senior staff, you'll get actionable advice for approaching various obstacles in your path. This book is ideal whether you're a new manager, a mentor, or a more experienced leader looking for fresh advice. Pick up this book and learn how to become a better manager and leader in your organization. Begin by exploring what you expect from a manager Understand what it takes to be a good mentor, and a good tech lead Learn how to manage individual members while remaining focused on the entire team Understand how to manage yourself and avoid common pitfalls that challenge many leaders Manage multiple teams and learn how to manage managers Learn how to build and bootstrap a unifying culture in teams

Google pioneered the discipline of Site Reliability Engineering, applying reliability to the entire user journey for consumer, enterprise, and infrastructure systems. In the years since, many organizations have followed suit, guided by the tenets laid out in this practical book. This fully revised edition brings Site Reliability Engineering up-to-date with fresh insights on engineering techniques, organizational processes, and case studies that will help you promote and implement greater reliability throughout the engineering lifecycle.In this collection of essays and articles, key members of Google's Site Reliability Engineering team explore the company's current SRE practices and explain how they've evolved in the decade since the initial publication. New updates cover the value of reliability, cloud reliability, and the impact of AI. You'll learn the principles and practices that enable Google engineers to make some of the world's largest systems scalable, reliable, and efficient-lessons directly applicable to your organization.Train new Site Reliability Engineers based on the latest practices in the fieldDevelop engineering organizations that support reliability as a featureBuild online services that incorporate reliability principlesUse AI to improve SRE across the organization and optimize critical areas such as automation and incident detection

Generative AI has revolutionized how organizations tackle problems, accelerating the journey from concept to prototype to solution. While these applications enhance efficiency, they often require extensive planning, drafting, and revising to complete complex tasks. By combining many of these actions, AI agents offer greater autonomy and efficiency, but understanding and deploying them remains a challenge for many organizations, especially as technology and research rapidly develops.This book is your indispensable guide through this intricate and fast-moving landscape. Author Michael Albada provides a practical and research-based approach to designing and implementing single- and multi-agent systems. It simplifies the complexities and equips you with the tools to move from concept to solution efficiently. By the end, you'll:Understand the distinct features of foundation model-enabled AI agentsDiscover the core components and design principles of AI agentsExplore design trade-offs and implement effective multi-agent systemsDesign and deploy tailored AI solutions, enhancing efficiency and innovation in your field

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the Jupyter notebook and IPython shell for exploratory computingLearn basic and advanced features in NumPyGet started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples

As AI agents move from research labs into production, engineering teams face mounting challenges-fragile tools, rising inference costs, erratic behavior, and unmet expectations. AI Agents: The Definitive Guide addresses what most books avoid: how to design, deploy, and maintain autonomous LLM agents that actually work in the real world. Written by Nicole Koenigstein, a leader in agentic AI with deep experience across finance, research, and engineering, this book offers the practical, system-level foundations needed to build robust, scalable, and secure agentic systems.Whether you're tasked with making agent prototypes production-ready or building mission-critical automation from the ground up, this book guides you through every layer of the stack. It covers architectures, tool integration, performance optimization, safety strategies, and advanced evaluation, with a relentless focus on reliability and long-term value.Design agent systems using modern frameworks like Reflexion, ReAct, and LangGraphOptimize deployment with advanced model techniques and GPU-aware inference strategiesSecurely integrate agents with tools using sandboxing, API contracts, and interface isolationBuild rigorous agent evaluation pipelines and address "agent-washing" failuresScale fault-tolerant agents across orchestration platforms like Ray and KubernetesApply debugging and monitoring practices to ensure safe agent reasoning and execution

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 experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach.AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications.Understand what AI engineering is and how it differs from traditional machine learning engineeringLearn the process for developing an AI application, the challenges at each step, and approaches to address themExplore various model adaptation techniques, including prompt engineering, RAG, fine-tuning, agents, and dataset engineering, and understand how and why they workExamine the bottlenecks for latency and cost when serving foundation models and learn how to overcome themChoose the right model, dataset, evaluation benchmarks, and metrics for your needsChip Huyen works to accelerate data analytics on GPUs at Voltron Data. Previously, she was with Snorkel AI and NVIDIA, founded an AI infrastructure startup, and taught Machine Learning Systems Design at Stanford. She's the author of the book Designing Machine Learning Systems, an Amazon bestseller in AI.AI Engineering builds upon and is complementary to Designing Machine Learning Systems (O'Reilly).

AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today.You'll learn how to use the power of pretrained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large numbers of text documents; and use existing libraries and pretrained models for text classification, search, and clusterings.This book also shows you how to:Build advanced LLM pipelines to cluster text documents and explore the topics they belong toBuild semantic search engines that go beyond keyword search with methods like dense retrieval and rerankersLearn various use cases where these models can provide valueUnderstand the architecture of underlying Transformer models like BERT and GPTGet a deeper understanding of how LLMs are trainedOptimize LLMs for specific applications with methods such as generative model fine-tuning, contrastive fine-tuning, and in-context learning

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started.Use scikit-learn to track an example machine learning project end to endExplore several models, including support vector machines, decision trees, random forests, and ensemble methodsExploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detectionDive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, and transformersUse TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learningTrain neural nets using multiple GPUs and deploy them at scale using Google's Vertex AI

What will you learn from this book?You know you don't want to reinvent the wheel, so you look to Design Patterns: the lessons learned by those who've faced the same software design problems. With Design Patterns, you get to take advantage of the best practices and experience of others so you can spend your time on something more challenging. Something more fun. This book shows you the patterns that matter, when to use them and why, how to apply them to your own designs, and the object-oriented design principles on which they're based. Join hundreds of thousands of developers who've improved their object-oriented design skills through Head First Design Patterns.What's so special about this book?If you've read a Head First book, you know what to expect: a visually rich format designed for the way your brain works. With Head First Design Patterns, 2E you'll learn design principles and patterns in a way that won't put you to sleep, so you can get out there to solve software design problems and speak the language of patterns with others on your team.

To stay competitive in today’s market, organizations need to adopt a culture of customer-centric practices that focus on outcomes rather than outputs. Companies that live and die by outputs often fall into the "build trap," cranking out features to meet their schedule rather than the customer’s needs. In this book, Melissa Perri explains how laying the foundation for great product management can help companies solve real customer problems while achieving business goals. By understanding how to communicate and collaborate within a company structure, you can create a product culture that benefits both the business and the customer. You’ll learn product management principles that can be applied to any organization, big or small. In five parts, this book explores: Why organizations ship features rather than cultivate the value those features represent How to set up a product organization that scales How product strategy connects a company’s vision and economic outcomes back to the product activities How to identify and pursue the right opportunities for producing value through an iterative product framework How to build a culture focused on successful outcomes over outputs

Don't waste time bending Python to fit patterns you've learned in other languages. Python's simplicity lets you become productive quickly, but often this means you aren't using everything the language has to offer. With the updated edition of this hands-on guide, you'll learn how to write effective, modern Python 3 code by leveraging its best ideas.Discover and apply idiomatic Python 3 features beyond your past experience. Author Luciano Ramalho guides you through Python's core language features and libraries and teaches you how to make your code shorter, faster, and more readable.Complete with major updates throughout, this new edition features five parts that work as five short books within the book:Data structures: Sequences, dicts, sets, Unicode, and data classesFunctions as objects: First-class functions, related design patterns, and type hints in function declarationsObject-oriented idioms: Composition, inheritance, mixins, interfaces, operator overloading, protocols, and more static typesControl flow: Context managers, generators, coroutines, async/await, and thread/process poolsMetaprogramming: Properties, attribute descriptors, class decorators, and new class metaprogramming hooks that replace or simplify metaclasses

In today's environment of partial attention and isolating remote work, few things are more satisfying than group experiences that produce powerful, meaningful connections and output. But this kind of enlivening, collective work doesn't happen by chance. It must be consciously designed and purposefully activated--;in a team, an organization, and a culture. The good news is that making space for this kind of work doesn't have to be hard. There's a technique available to everyone, with no special certification required: gamestorming.This substantial update to the best-selling O'Reilly book now includes three new chapters and 95 games. The authors identified and curated techniques from some of the world's most innovative professionals as well as inventing games of their own. This book is the result: a unique collection of approaches to simultaneously ignite engagement and level-up creative teamship while bringing agility and structure to gatherings at work in person and online.Shorten meetings and make them significantly more productiveIncrease efficacy and engagement in strategic thinking and problem-solvingEnhance connection and communication across team membersElevate collaboration and uncover surprising solutions to sticky problemsGenerate better ideas and significantly improve remote work experiences

Make: Electronics explores the properties and applications of discrete components that are the fundamental building blocks of circuit design. Understanding resistors, capacitors, transistors, inductors, diodes, and integrated circuit chips is essential even when using microcontrollers. Make: Electronics teaches the fundamentals and also provides advice on the tools and supplies that are necessary. Component kits are available, specifically developed for the third edition.

Now in full color, the 10th anniversary edition of this classic book takes you deep into the influences that underlie modern video games, and examines the elements they share with traditional games such as checkers. At the heart of his exploration, veteran game designer Raph Koster takes a close look at the concept of fun and why it's the most vital element in any game. Why do some games become boring quickly, while others remain fun for years? How do games serve as fundamental and powerful learning tools? Whether you're a game developer, dedicated gamer, or curious observer, this illustrated, fully updated edition helps you understand what drives this major cultural force, and inspires you to take it further. You'll discover that: Games play into our innate ability to seek patterns and solve puzzles Most successful games are built upon the same elements Slightly more females than males now play games Many games still teach primitive survival skills Fictional dressing for modern games is more developed than the conceptual elements Truly creative designers seldom use other games for inspiration Games are beginning to evolve beyond their prehistoric origins

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you will learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You will understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, governance, and deployment that are critical in any data environment regardless of the underlying technology. This book will help you: Assess data engineering problems using an end-to-end data framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle

Designing good application interfaces isn’t easy now that companies need to create compelling, seamless user experiences across an exploding number of channels, screens, and contexts. In this updated third edition, you’ll learn how to navigate through the maze of design options. By capturing UI best practices as design patterns, this best-selling book provides solutions to common design problems.You’ll learn patterns for mobile apps, web applications, and desktop software. Each pattern contains full-color examples and practical design advice you can apply immediately. Experienced designers can use this guide as an idea sourcebook, and novices will find a road map to the world of interface and interaction design.Understand your users before you start designingBuild your software’s structure so it makes sense to usersDesign components to help users complete tasks on any deviceLearn how to promote wayfinding in your softwarePlace elements to guide users to information and functionsLearn how visual design can make or break product usabilityDisplay complex data with artful visualizations

Learn how to use R to turn data into insight, knowledge, and understanding. Ideal for current and aspiring data scientists, this book introduces you to doing data science with R and RStudio, as well as the tidyverse-a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly.You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Each section in this edition includes exercises to help you practice what you've learned along the way.Updated for the latest tidyverse best practices, new chapters dive deeper into visualization and data wrangling, show you how to get data from spreadsheets, databases, and websites, and help you make the most of new programming tools.You'll learn how to:Visualize-create plots for data exploration and communication of resultsTransform-discover types of variables and the tools you can use to work with themImport-get data into R and in a form convenient for analysisProgram-learn R tools for solving data problems with greater clarity and easeCommunicate-integrate prose, code, and results with Quarto

Messy code is a nuisance. "Tidying" code, to make it more readable, requires breaking it up into manageable sections. In this practical guide, author Kent Beck, creator of Extreme Programming and pioneer of software patterns, suggests when and where you might apply tidyings to improve your code while keeping the overall structure of the system in mind.Instead of trying to master tidying all at once, this book lets you try out a few examples that make sense for your problem. If you have a big function containing many lines of code, you'll learn how to logically divide it into smaller chunks. Along the way, you'll learn the theory behind software design: coupling, cohesion, discounted cash flows, and optionality.This book helps you:Understand the basic theory of how software design works and the forces that act on itExplore the difference between changes to a system's behavior and changes to its structureImprove your programming experience by sometimes tidying first and sometimes tidying afterLearn how to make large changes in small, safe stepsApproach design as a human activity with diverging incentives

Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz's popular training course, this updated sixth edition will help you quickly write efficient, high-quality code with Python. It's an ideal way to begin, whether you're new to programming or a professional developer versed in other languages.Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow self-paced tutorial gets you started with Python 3.12 and all other releases in use today. With a pragmatic focus on what you need to know, it also introduces some advanced language features that have become increasingly common in Python code.This book helps you:Explore Python's built-in object types such as strings, lists, dictionaries, and filesCreate and process objects with Python statements, and learn Python's syntax modelUse functions and functional programming to avoid redundancy and maximize reuseOrganize code into larger components with modules and packagesCode robust programs with Python's exception handling and development toolsApply object-oriented programming and classes to make code customizableSurvey advanced Python tools including decorators, descriptors, and metaclassesWrite idiomatic Python code that runs portably across a wide variety of platforms

AI is transforming software development, shifting programmers from writing code to collaborating with AI in an intent-driven workflow-this is vibe coding. Vibe Coding: The Future of Programming explores how AI-powered coding assistants like GitHub Copilot and OpenAI Codex are reshaping the way we build software, from automating routine coding tasks to influencing architecture and design decisions.Written by Addy Osmani, this guide provides developers, tech leads, and organizations with practical strategies to integrate AI into their workflows effectively. Learn how to refine AI-generated code, master prompt engineering, and explore advanced techniques like model fine-tuning and multi-agent coding systems. Whether you're adopting AI tools today or preparing for the future of software engineering, this book offers insights and hands-on examples to keep your skills sharp in this evolving landscape.Understand how AI-assisted development is reshaping programmingMaster techniques for refining, validating, and debugging AI-generated codeExplore multi-agent coding systems and AI-driven software workflowsFuture-proof your career by adapting to AI's growing role in development

Building software is harder than ever. As a developer, you not only have to chase ever-changing technological trends but also need to understand the business domains behind the software. This practical book provides you with a set of core patterns, principles, and practices for analyzing business domains, understanding business strategy, and, most importantly, aligning software design with its business needs.Author Vlad Khononov shows you how these practices lead to robust implementation of business logic and help to future-proof software design and architecture. You'll examine the relationship between domain-driven design (DDD) and other methodologies to ensure you make architectural decisions that meet business requirements. You'll also explore the real-life story of implementing DDD in a startup company.With this book, you'll learn how to:Analyze a company's business domain to learn how the system you're building fits its competitive strategyUse DDD's strategic and tactical tools to architect effective software solutions that address business needsBuild a shared understanding of the business domains you encounterDecompose a system into bounded contextsCoordinate the work of multiple teamsGradually introduce DDD to brownfield projects

JavaScript is the programming language of the web and is used by more software developers today than any other programming language. For nearly 25 years this best seller has been the go-to guide for JavaScript programmers. The seventh edition is fully updated to cover the 2020 version of JavaScript, and new chapters cover classes, modules, iterators, generators, Promises, async/await, and metaprogramming. You'll find illuminating and engaging example code throughout.This book is for programmers who want to learn JavaScript and for web developers who want to take their understanding and mastery to the next level. It begins by explaining the JavaScript language itself, in detail, from the bottom up. It then builds on that foundation to cover the web platform and Node.js. Topics include:Types, values, variables, expressions, operators, statements, objects, and arraysFunctions, classes, modules, iterators, generators, Promises, and async/awaitJavaScript's standard library: data structures, regular expressions, JSON, i18n, etc.The web platform: documents, components, graphics, networking, storage, and threadsNode.js: buffers, files, streams, threads, child processes, web clients, and web serversTools and language extensions that professional JavaScript developers rely on

TypeScript is a typed superset of JavaScript with the potential to solve many of the headaches for which JavaScript is famous. But TypeScript has a learning curve of its own, and understanding how to use it effectively takes time and practice. Using the format popularized by Effective C++ and Effective Java (both Addison-Wesley), this practical book features 83 items that give specific advice on what to do and what not to do, and how to think about the language.Author Dan Vanderkam shows you how to apply each item's advice through concrete examples. This book will help you advance from a beginning or intermediate user familiar with TypeScript basics to an expert who knows how to use the language well.Updated for TypeScript 5, this second edition includes two new chapters on type-level programming and TypeScript recipes.Learn the nuts and bolts of TypeScript's type systemUse type inference to get full safety with a minimum of type annotationsDesign types to make your code safer and more understandableModel complex APIs using generic types and type-level programmingUnderstand how dependencies and type declaration files work in TypeScriptSuccessfully migrate your JavaScript code base to TypeScript

When you have questions about C# 12 or .NET 8, this best-selling guide has the answers you need. C# is a language of unusual flexibility and breadth, and with its continual growth, there's always so much more to learn. In the tradition of O'Reilly's Nutshell guides, this thoroughly updated edition is simply the best one-volume reference to the C# language available today.Aimed at intermediate and advanced programmers, this is a book whose explanations get straight to the point, covering C#, the CLR, and the core .NET libraries in depth, without long intros or bloated samples.Get up to speed on C# from syntax and variables to advanced topics such as pointers, closures, and patternsDig deep into LINQ, with three chapters dedicated to the topicExplore concurrency and asynchrony, advanced threading, and parallel programmingWork with .NET features, including regular expressions, networking, assemblies, spans, cryptography and reflection.emit