Search results for ""O'Reilly""

Getting data across platforms and formats is a cornerstone of present-day applications development. ADO: ActiveX Data Objects is both an introduction and a complete reference to ADO (ActiveX Data Objects), Microsoft's universal data access solution. You'll learn how to easily access data in multiple formats--such as email messages, Access databases, Word documents, and SQL databases--even on different platforms, without spending extra time learning every last detail about each format. Author Jason Roff shows by example how to use ADO with your programming language of choice to save programming time, so you can concentrate on the content and quality of your application rather than the nitty-gritty of specific data formats. ADO: ActiveX Data Objects includes:; Chapters dedicated to the Connection, Recordset, Field, and Command objects and the Properties collection; A complete, detailed reference listing every ADO object, method, property, and event, in convenient alphabetical order; Chapters on ADO architecture, data shaping, the ADO Event Model; An appendix containing enumeration tables used by ADO objects and collections, listed alphabetically; Brief introductions to RDS, ADO.N ET, and SQL ADO: ActiveX Data Objects is a versatile one-stop guide to both the theory and practice of programming with ADO through Version 2.6. The thorough reference section and topic-specific chapters will help you find quick answers about the details of objects, collections, methods, and properties of ADO. And the abundance of practical code examples will give you a good grasp of how to use ADO's strong points most effectively.

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This volume is an introduction to Java's component architecture. It describes how to write Beans, which are software components that can be used in visual programming environments. This book discusses event adapters, serialization, introspection, property editors, and customizers, and shows how to use Beans within ActiveX controls.

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Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This revised third edition--updated for Cassandra 4.0 and new developments in the Cassandra ecosystem, including deployments in Kubernetes with K8ssandra--provides technical details and practical examples to help you put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. Developers, DBAs, and application architects looking to solve a database scaling issue or future-proof an application will learn how to harness Cassandra's speed and flexibility. Understand Cassandra's distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh (the CQL shell) Create a working data model and compare it with an equivalent relational model Design and develop applications using client drivers Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra onsite, in the cloud, or with Docker and Kubernetes Integrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene

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Learn the core concepts of Vue.js, the modern JavaScript framework for building frontend applications and interfaces from scratch. Through concise, practical, and clear examples, this book takes web developers step-by-step through the tools and libraries in the Vue.js ecosystem and how to use them to create complete applications for real-world web projects. Author Maya Shavin explains how to create a complete application development process using a variety of tools in the Vue.js library. You'll learn how to handle data communication between components with Pinia architecture, develop a manageable routing system for a frontend project to control the application flow, and produce basic animation effects to create a better user experience. This book also shows you how to: Create reusable and lightweight component systems using Vue.js Bring reactivity to your existing static application Set up a project using Vite.js, a build tool for frontend project code management Build an interactive state management system for a frontend application with Pinia Connect external data from the server to your Vue application Control the application flow with static and dynamic routing using Vue Router Fully test your application using Vitest and Playwright

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Give your organization the data protection it deserves, without the uncertainty and cost overruns experienced by your predecessors or other companies. System and network administrators today have their work cut out for them to protect physical and virtual machines in the data center and the cloud, mobile devices including laptops and tablets, SaaS services like Microsoft 365, Google Workspace, and Salesforce, and any persistent data created by Kubernetes and container workloads. To help you navigate the breadth and depth of this challenge, this book presents several solutions so you can determine which one is right for your company. You'll learn the unique requirements that each workload presents, then explore various categories of commercial backup hardware, software, and services available to protect these data sources, including the advantages and disadvantages of each approach. Learn the workload types that your organization should be backing up Explore the hardware, software, and services you can use to back up your systems Understand what's wrong with your current data protection system Pair your backed-up workloads to the appropriate backup system Learn the adjustments you need to make to make your backups better, without wasting money

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The cloud promises cost savings, agility, and more. But the increasing complexity of modern IT systems often prevents businesses from realizing the outcomes they sought by moving to the cloud in the first place. At the core of this complexity is technical debt. Ad hoc decisions, traditional approaches, and "quick and dirty" solutions add up to fragile, more complex systems (and organizations)--reducing the pace of change, driving up costs, and degrading security. To succeed in the cloud, you first have to manage the problems IT complexity creates. This practical guide will help. If you're tasked with designing, delivering, or approving IT systems that support business growth, this book will teach you the principles and strategies you need to break out of silos, reassess traditional thinking, provide the business a better competitive position, and achieve cloud success across the company. You'll learn: How to assess your current IT environment to identify complexity-centered risks How to structure cross-functional teams to reduce friction points How to create a framework for IT investments that's aligned with your business goals How to measure your outcomes for continued success

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This practical book provides a detailed explanation of the zero trust security model. The updated edition offers more scenarios, real-world examples, and in-depth explanations of key concepts to help you fully comprehend the zero trust security architecture.

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Even if you're familiar with C# syntax, knowing how to combine various language features is a critical skill when you're building applications. This cookbook is packed full of recipes to help you solve issues for C# programming tasks you're likely to encounter. You'll learn tried-and-true techniques to help you achieve greater productivity and improve the quality of your code. Author and independent consultant Joe Mayo shares some of the most important practices you'll need to be successful as a C# developer. Each section of this cookbook describes some useful facet of the C# programming language. These recipes--the result of many years of experience--are proven concepts for solving real-world problems with C#. Recipes in this book will help you: Set up your project, manage object lifetime, and establish patterns Improve code quality through maintainability, error prevention, and correct syntax Use LINQ to Objects for in-memory data manipulation and querying Understand the differences between dynamic programming and reflection Apply several async programming features you may not be aware of Work with data using newer libraries and algorithms Learn different ways to use new C# features, such as pattern matching and records

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For MySQL, the price of popularity comes with a flood of questions from users on how to solve specific data-related issues. That's where this cookbook comes in. When you need quick solutions or techniques, this handy resource provides scores of short, focused pieces of code, hundreds of worked-out examples, and clear, concise explanations for programmers who don't have the time (or expertise) to resolve MySQL problems from scratch. In this updated fourth edition, authors Sveta Smirnova and Alkin Tezuysal provide more than 200 recipes that cover powerful features in both MySQL 5.7 and 8.0. Beginners as well as professional database and web developers will dive into topics such as MySQL Shell, MySQL replication, and working with JSON. You'll learn how to: Connect to a server, issue queries, and retrieve results Retrieve data from the MySQL Server Store, retrieve, and manipulate strings Work with dates and times Sort query results and generate summaries Assess the characteristics of a dataset Write stored functions and procedures Use stored routines, triggers, and scheduled events Perform basic MySQL administration tasks Understand MySQL monitoring fundamentals

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The cloud is becoming the de facto home for companies ranging from enterprises to startups. Moving to the cloud means moving your applications from monolith to microservices. But once you do, running and maintaining these services brings its own level of complexity. The answer? Modularity, deployability, observability, and self-healing capacity through cloud native development. With this practical book, Nishant Singh and Michael Kehoe show you how to build a true cloud native infrastructure using Microsoft Azure or another cloud computing solution by following guidelines from the Cloud Native Computing Foundation (CNCF). DevOps and site reliability engineers will learn how adapting applications to cloud native early in the design phase helps you fully utilize the elasticity and distributed nature of the cloud. This book helps you explore: Why go cloud native? How to use infrastructure as code What it takes to containerize an application Why and how Kubernetes is the "grand orchestrator" How to create a Kubernetes cluster on Azure How observability complements monitoring How to use service discovery and a service mesh to find new territories How networking and policy management serve as gatekeepers How distributed databases and storage work

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Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how to compare results from ML models with results obtained by traditional financial risk models. Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models. Review classical time series applications and compare them with deep learning models Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning Revisit and improve market risk models (VaR and expected shortfall) using machine learning techniques Develop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML models Capture different aspects of liquidity with a Gaussian mixture model Use machine learning models for fraud detection Identify corporate risk using the stock price crash metric Explore a synthetic data generation process to employ in financial risk

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Tap into the wisdom of experts to learn what every UX practitioner needs to know. With 97 short and extremely useful articles, you'll discover new approaches to old problems, pick up road-tested best practices, and hone your skills through sound advice. Working in UX involves much more than just creating user interfaces. UX teams struggle with understanding what's important, which practices they should know deeply, and what approaches aren't helpful at all. With these 97 concise articles, editor Dan Berlin presents a wealth of advice and knowledge from experts who have practiced UX throughout their careers. Bring Themes to Exploratory Research--Shanti Kanhai Design for Content First--Marli Mesibov Design for Universal Usability--Ann Chadwick-Dias Be Wrong on Purpose--Skyler Ray Taylor Diverse Participant Recruiting Is Critical to Authentic User Research--Megan Campos Put On Your InfoSec Hat to Improve Your Designs--Julie Meridian Boost Your Emotional Intelligence to Move from Good to Great UX--Priyama Barua

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What will you learn from this book? If you have an idea for a killer Android app, this fully revised and updated edition will get you up and running in a jiffy. You'll go beyond syntax and how-to manuals and learn how to think like a great Android developer. This hands-on book teaches you everything from designing layouts to the latest features of Android Jetpack, including the Room persistence library, LiveData and the Navigation component. It's like having an experienced Android developer sitting right next to you! If you have some Kotlin know-how, you're ready to get started. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Android Development uses a visually rich format to engage your mind rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multisensory learning experience is designed for the way your brain really works.

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Networking and Kubernetes is an essential guide for anyone who wants to deploy, manage, or troubleshoot a production scale Kubernetes network. Understanding Kubernetes clusters is not enough to operate Kubernetes at scale. Every layer of the stack--the network, operating system, and Kubernetes--depends on the layer below. Successful administrators need to understand each layer and how it works across deployments on-prim, in the cloud, and with managed services. Networking and Kubernetes clearly guides administrators through the layers of complexity and abstraction that come with running a Kubernetes network. It covers: The Kubernetes networking model The CNCF Container Network Interface Project and how to choose the best interface for your clusters The networking and Linux primitives that power Kubernetes How to quickly troubleshoot networking issues and prevent downtime Cloud networking and Kubernetes with the three major providers: AWS, GCP, and Azure The pros and cons of various network tools--and how to select the best ones for your stack

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Among the text editors being used in the programming community, perhaps the most important family is vi and its derivatives. With this updated edition, Unix and Linux users will learn text editing basics for both vi and Vim ("vi improved") before moving on to advanced editing tools for each editor. Authors Arnold Robbins and Elbert Hannah cover the latest major releases of Vim, including 8.0 and 8.2. If you're a programmer or computer analyst, or you work with browsers or command-line interfaces, using Vim can speed up your work and make complex tasks easier. You'll examine multiwindow editing, global search and replacement, and power tools for programmers, and learn how to write interactive macros and scripts to extend the editor--all in the easy-to-follow style that's made this book a classic. Go beyond the basics to learn which vi commands fit your specific needs Learn advanced vi tools that shift most of the editing burden to the computer Explore Vim tools that provide major improvements over vi Examine Vim's multiwindow editing feature, a significant upgrade over vi Use Vim scripts to customize and tailor Vim to your needs Look at Vim in modern GUI environments with Graphical Vim (gvim) See Vim in the broader programming milieu, including using it as an IDE

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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 up your skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with Amazon SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, and more Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more

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This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 80 tools--useful whether you work with Windows, macOS, or Linux. You'll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you're comfortable processing data with Python or R, you'll learn how to greatly improve your data science workflow by leveraging the command line's power. This book is ideal for data scientists, analysts, and engineers; software and machine learning engineers; and system administrators. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on text, CSV, HTM, XML, and JSON files Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow Create reusable command-line tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines Model data with dimensionality reduction, clustering, regression, and classification algorithms

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For self-service data preparation, Tableau Prep is relatively easy to use—as long as you know how to clean and organize your datasets. Carl Allchin, from The Information Lab in London, gets you up to speed on Tableau Prep through a series of practical lessons that include methods for preparing, cleaning, automating, organizing, and outputting your datasets. Based on Allchin’s popular blog, Preppin’ Data, this practical guide takes you step-by-step through Tableau Prep’s fundamentals. Self-service data preparation reduces the time it takes to complete data projects and improves the quality of your analyses. Discover how Tableau Prep helps you access your data and turn it into valuable information. Know what to look for when you prepare data Learn which Tableau Prep functions to use when working with data fields Analyze the shape and profile of your dataset Output data for analysis and learn how Tableau Prep automates your workflow Learn how to clean your dataset using Tableau Prep functions Explore ways to use Tableau Prep techniques in real-world scenarios Make your data available to others by managing and documenting the output

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With over 75 million downloads per month, Spring Boot is the most widely used Java framework available. Its ease and power have revolutionized application development from monoliths to microservices. Yet Spring Boot's simplicity can also be confounding. How do developers learn enough to be productive immediately? This practical book shows you how to use this framework to write successful mission-critical applications. Mark Heckler from VMware, the company behind Spring, guides you through Spring Boot's architecture and approach, covering topics such as debugging, testing, and deployment. If you want to develop cloud native Java or Kotlin applications with Spring Boot rapidly and effectively (using reactive programming, building APIs, and creating database access of all kinds) this book is for you. Learn how Spring Boot simplifies cloud native application development and deployment Build reactive applications and extend communication across the network boundary to create distributed systems Understand how Spring Boot's architecture and approach increase developer productivity and application portability Deploy Spring Boot applications for production workloads rapidly and reliably Monitor application and system health for optimal performance and reliability Debug, test, and secure cloud-based applications painlessly

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Apple gives macOS new features and improvements right on your desktop and under the hood with Catalina—aka OS X 10.15. With this updated guide, you’ll learn how to use your iPad as a second screen, work with iPad apps on your Mac, and use Screen Time on your Mac. This new edition of the #1 bestselling Mac book shows you how to use the revamped apps for Music, Podcasts, and TV. Loaded with illustrations, step-by-step instructions, tips, and tricks, this book from David Pogue—Missing Manual series creator, New York Times columnist, and Emmy-winning tech correspondent for CNBC, CBS, and NPR—covers everything Catalina has to offer with lots of humor and technical insight.

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If you’re among the Python developers put off by asyncio’s complexity, it’s time to take another look. Asyncio is complicated because it aims to solve problems in concurrent network programming for both framework and end-user developers. The features you need to consider are a small subset of the whole asyncio API, but picking out the right features is the tricky part. That’s where this practical book comes in. Veteran Python developer Caleb Hattingh helps you gain a basic understanding of asyncio’s building blocks—enough to get started writing simple event-based programs. You’ll learn why asyncio offers a safer alternative to preemptive multitasking (threading) and how this API provides a simple way to support thousands of simultaneous socket connections. Get a critical comparison of asyncio and threading for concurrent network programming Take an asyncio walk-through, including a quickstart guide for hitting the ground looping with event-based programming Learn the difference between asyncio features for end-user developers and those for framework developers Understand asyncio’s new async/await language syntax, including coroutines and task and future APIs Get detailed case studies (with code) of some popular asyncio-compatible third-party libraries

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Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail

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Learn how to build a real-world serverless application in the cloud that's reliable, secure, maintainable, and scalable. If you have experience building web applications on traditional infrastructure, this hands-on guide shows you how to get started with Cloud Run, a container-based serverless product on Google Cloud. Through the course of this book, you'll learn how to deploy several example applications that highlight different parts of the serverless stack on Google Cloud. Combining practical examples with fundamentals, this book will appeal to developers who are early in their learning journey as well as experienced practitioners. Build a serverless application with Google Cloud Run Learn approaches for building containers with (and without) Docker Explore Google Cloud's managed relational database: Cloud SQL Use HTTP sessions to make every user's experience unique Explore identity and access management (IAM) on Cloud Run Provision Google Cloud resources using Terraform Learn how to handle background task scheduling on Cloud Run Move your service from Cloud Run to Knative Serving with little effort

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Whether your company is considering serverless computing or has already made the decision to adopt this model, this practical book is for you. Author Jason Katzer shows early- and mid-career developers what's required to build and ship maintainable and scalable services using this model. With this book, you'll learn how to build a modern production system in the cloud, viewed through the lens of serverless computing. You'll discover how serverless can free you from the tedious task of setting up and maintaining systems in production. You'll also explore new ways to level up your career and design, develop, and deploy with confidence. In three parts, this book includes: The Path to Production: Examine the ins and outs of distributed systems, microservices, interfaces, and serverless architecture and patterns The Tools: Dive into monitoring, observability and alerting, logging, pipelines, automation, and deployment Concepts: Learn how to design security and privacy, how to manage quality through testing and staging, and how to plan for failure

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Early system administration required in-depth knowledge of a variety of services on individual systems. Now, the job is increasingly complex and different from one company to the next with an ever-growing list of technologies and third-party services to integrate. How does any one individual stay relevant in systems and services? This practical guide helps anyone in operations -sysadmins, automation engineers, IT professionals, and site reliability engineers - understand the essential concepts of the role today. Collaboration, automation, and the evolution of systems change the fundamentals of operations work. No matter where you are in your journey, this book provides you the information to craft your path to advancing essential system administration skills. Author Jennifer Davis provides examples of modern practices and tools with recommended materials to advance your skills. Topics include: Development and testing: Version control, fundamentals of virtualization and containers, testing, and architecture review Deploying and configuring services: Infrastructure management, networks, security, storage, serverless, and release management Scaling administration: Monitoring and observability, capacity planning, log management and analysis, and security and compliance

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Every day, thousands of passionate developers come up with new startup ideas but lack the branding know-how to make them thrive. If you count yourself among them, Lean Branding is here to help. This practical toolkit helps you build your own robust, dynamic brands that generate conversion. You’ll find over 100 DIY branding tactics and inspiring case studies, and step-by-step instructions for building and measuring 25 essential brand strategy ingredients, from logo design to demo-day pitches, using The Lean Startup methodology’s Build-Measure-Learn loop. Learn exactly what a brand is—and what it isn’t Build a minimal set of brand ingredients that are viable in the marketplace: brand story, brand symbols, and brand strategy Measure your brand ingredients by using meaningful metrics to see if they meet your conversion goals Pivot your brand ingredients in new directions based on what you’ve learned—by optimizing rather than trashing Focus specifically on brand story, symbols, or strategy by following the Build-Measure-Learn chapters that apply

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Get professionally developed and curated recipes for 20 of the most common tasks for functionality in modern native iOS and Android applications. With this practical book, developers can use an easily translatable set of instructions for completing routine functionality in both platforms in a way that follows best practices. Authors Shaun Lewis and Mike Dunn provide step-by-step direction to help you create a fully-functional application using modern practices and designs that will utilize those tasks. The development of the apps will be laid out side-by-side, so that the friction usually involved in switching between platforms while developing is greatly reduced. By the end of this book, you’ll have developed apps for both iOS and Android with exactly the same core features, as well as some additional features that are relevant and unique to each app’s operating system.

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Digital product research doesn't have to be difficult, take a long time, or cost a lot of money. Nor should it be a job solely for scientists or expert researchers. In this practical book, Aras Bilgen, C. Todd Lombardo, and Michael Connors demonstrate how your entire team can conduct effective product research within a couple of weeks--easily, cheaply, and without compromising quality. Drawing from decades of experience in product development, the authors lay out nine simple rules that combine user research, market research, and product analytics to quickly discover insights and build products customers truly need. Recognize and avoid common research pitfalls Switch to the insight-making mindset that underlies all successful research efforts Find out how to look at data, formulate the right questions, and pick the right research method Learn interview techniques and research skills Analyze for insights collaboratively while avoiding bias Inspire action with your insights through powerful presentations and prototypes Learn how to involve a wide variety of stakeholders in research, from developers to executives Discover how you can make research a habit, not a one-off effort

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If you’re just learning how to program, Julia is an excellent JIT-compiled, dynamically typed language with a clean syntax. This hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch. Designed from the beginning for high performance, Julia is a general-purpose language ideal for not only numerical analysis and computational science but also web programming and scripting. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Julia is perfect for students at the high school or college level as well as self-learners and professionals who need to learn programming basics. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand types, methods, and multiple dispatch Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design and data structures through case studies

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Until recently, learning CoreDNS required reading the code or combing through the skimpy documentation on the website. No longer. With this practical book, developers and operators working with Docker or Linux containers will learn how to use this standard DNS server with Kubernetes. John Belamaric, senior staff software engineer at Google, and Cricket Liu, chief DNS architect at Infoblox, show you how to configure CoreDNS using real-world configuration examples to achieve specific purposes. You’ll learn the basics of DNS, including how it functions as a location broker in container environments and how it ties into Kubernetes. Dive into DNS theory: the DNS namespace, domain names, domains, and zones Learn how to configure your CoreDNS server Manage and serve basic and advanced zone data with CoreDNS Configure CoreDNS service discovery with etcd and Kubernetes Learn one of the most common use cases for CoreDNS: the integration with Kubernetes Manipulate queries and responses as they flow through the plug-in chain Monitor and troubleshoot the availability and performance of your DNS service Build custom versions of CoreDNS and write your own plug-ins

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Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they’re used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. You’ll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today’s data Understand how popular graph algorithms work and how they’re applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark

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Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data

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Ready to dive into smart contract development for the blockchain? With this practical guide, experienced engineers and beginners alike will quickly learn the entire process for building smart contracts for Ethereum—the open source blockchain-based distributed computing platform. You’ll get up to speed with the fundamentals and quickly move into builder mode. Kevin Solorio, Randall Kanna, and Dave Hoover show you how to create and test your own smart contract, create a frontend for users to interact with, and more. It’s the perfect resource for people who want to break into the smart contract field but don’t know where to start. In four parts, this book helps you: Explore smart contract fundamentals, including the Ethereum protocol, Solidity programming language, and the Ethereum Virtual Machine Dive into smart contract development using Solidity and gain experience with Truffle framework tools for deploying and testing your contracts Use Web3 to connect your smart contracts to an application so users can easily interact with the blockchain Examine smart contract security along with free online resources for smart contract security auditing

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Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV. Drill reads data in HDFS or in cloud-native storage such as S3 and works with Hive metastores along with distributed databases such as HBase, MongoDB, and relational databases. Drill works everywhere: on your laptop or in your largest cluster. In this practical book, Drill committers Charles Givre and Paul Rogers show analysts and data scientists how to query and analyze raw data using this powerful tool. Data scientists today spend about 80% of their time just gathering and cleaning data. With this book, you’ll learn how Drill helps you analyze data more effectively to drive down time to insight. Use Drill to clean, prepare, and summarize delimited data for further analysis Query file types including logfiles, Parquet, JSON, and other complex formats Query Hadoop, relational databases, MongoDB, and Kafka with standard SQL Connect to Drill programmatically using a variety of languages Use Drill even with challenging or ambiguous file formats Perform sophisticated analysis by extending Drill’s functionality with user-defined functions Facilitate data analysis for network security, image metadata, and machine learning

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Despite popular forays into augmented and virtual reality in recent years, spatial computing still sits on the cusp of mainstream use. Developers, artists, and designers looking to enter this field today have few places to turn for expert guidance. In this book, Erin Pangilinan, Steve Lukas, and Vasanth Mohan examine the AR and VR development pipeline and provide hands-on practice to help you hone your skills. Through step-by-step tutorials, you’ll learn how to build practical applications and experiences grounded in theory and backed by industry use cases. In each section of the book, industry specialists, including Timoni West, Victor Prisacariu, and Nicolas Meuleau, join the authors to explain the technology behind spatial computing. In three parts, this book covers: Art and design: Explore spatial computing and design interactions, human-centered interaction and sensory design, and content creation tools for digital art Technical development: Examine differences between ARKit, ARCore, and spatial mapping-based systems; learn approaches to cross-platform development on head-mounted displays Use cases: Learn how data and machine learning visualization and AI work in spatial computing, training, sports, health, and other enterprise applications

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If you’re ready to get started with Raku (formerly Perl 6), this is the book you want, whether you’re a programmer, system administrator, or web hacker. Raku is a new language—a modern reinvention of Perl suitable for almost any task, from short fixes to complete web applications. This hands-on tutorial gets you started. Author brian d foy (Mastering Perl) provides a sophisticated introduction to this new programming language. Each chapter in this guide contains exercises to help you practice what you learn as you learn it. Other books may teach you to program in Raku, but this book will turn you into a Raku programmer. Learn how to work with: Numbers, strings, blocks, and positionals Files and directories and input/output Associatives, subroutines, classes, and roles Junctions and sets Regular expressions and built-in grammars Concurrency features: Promises, supplies, and channels Controlling external programs and other advanced features

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The introduction of functional programming concepts in Java SE 8 was a drastic change for this venerable object-oriented language. Lambda expressions, method references, and streams fundamentally changed the idioms of the language, and many developers have been trying to catch up ever since. This cookbook will help. With more than 70 detailed recipes, author Ken Kousen shows you how to use the newest features of Java to solve a wide range of problems. For developers comfortable with previous Java versions, this guide covers nearly all of Java SE 8, and includes a chapter focused on changes coming in Java 9. Need to understand how functional idioms will change the way you write code? This cookbook—chock full of use cases—is for you. Recipes cover: The basics of lambda expressions and method references Interfaces in the java.util.function package Stream operations for transforming and filtering data Comparators and Collectors for sorting and converting streaming data Combining lambdas, method references, and streams Creating instances and extract values from Java’s Optional type New I/O capabilities that support functional streams The Date-Time API that replaces the legacy Date and Calendar classes Mechanisms for experimenting with concurrency and parallelism

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How often do you hear people say things like this? "Our JavaScript is a mess, but we're thinking about using [framework of the month]." Like it or not, JavaScript is not going away. No matter what framework or "compiles-to-js" language or library you use, bugs and performance concerns will always be an issue if the underlying quality of your JavaScript is poor. Rewrites, including porting to the framework of the month, are terribly expensive and unpredictable. The bugs won't magically go away, and can happily reproduce themselves in a new context. To complicate things further, features will get dropped, at least temporarily. The other popular method of fixing your JS is playing "JavaScript Jenga," where each developer slowly and carefully takes their best guess at how the out-of-control system can be altered to allow for new features, hoping that this doesn't bring the whole stack of blocks down. This book provides clear guidance on how best to avoid these pathological approaches to writing JavaScript: Recognize you have a problem with your JavaScript quality. Forgive the code you have now, and the developers who made it. Learn repeatable, memorable, and time-saving refactoring techniques. Apply these techniques as you work, fixing things along the way. Internalize these techniques, and avoid writing as much problematic code to begin with. Bad code doesn't have to stay that way. And making it better doesn't have to be intimidating or unreasonably expensive.

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What can your organization gain by adopting HTTP/2? How about faster, simpler, and more robust websites and applications? This practical guide demonstrates how the latest version of the Hypertext Transfer Protocol can dramatically improve website and application performance. You'll take a deep dive into HTTP/2 details, and learn how this updated protocol is changing the web landscape. HTTP/1.1 has been the primary means of communicating data across the web for the past 20 years, but the level of interaction today has gone well beyond what people envisioned in 1997. With this book, authors Stephen Ludin and Javier Garza show you how HTTP/2 will help speed the execution of modern sites and applications. With this book, you'll explore: Performance challenges that led to the HTTP upgrade HTTP/2 in a nutshell, including benefits and transition methods Existing best practices and hacks to improve web performance HTTP/2 support for browsers, servers, proxies, and content delivery networks How the performance of sites using HTTP/2 compares to their HTTP/1.1 experience HTTP/2's effect on specific issues such as latency, packet loss, and Time to First Byte (TTFB)

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More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, you ll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm.Authors Ted Dunning and Ellen Friedman (Real World Hadoop) help you explore some of the best technologies to handle stream processing and analytics, with a focus on the upstream queuing or message-passing layer. To illustrate the effectiveness of these technologies, this book also includes specific use cases.Ideal for developers and non-technical people alike, this book describes: Key elements in good design for streaming analytics, focusing on the essential characteristics of the messaging layerNew messaging technologies, including Apache Kafka and MapR Streams, with links to sample codeTechnology choices for streaming analytics: Apache Spark Streaming, Apache Flink, Apache Storm, and Apache ApexHow stream-based architectures are helpful to support microservicesSpecific use cases such as fraud detection and geo-distributed data streamsTed Dunning is Chief Applications Architect at MapR Technologies, and active in the open source community. He currently serves as VP for Incubator at the Apache Foundation, as a champion and mentor for a large number of projects, and as committer and PMC member of the Apache ZooKeeper and Drill projects. Ted is on Twitter as @ted_dunning.Ellen Friedman, a committer for the Apache Drill and Apache Mahout projects, is a solutions consultant and well-known speaker and author, currently writing mainly about big data topics. With a PhD in Biochemistry, she has years of experience as a research scientist and has written about a variety of technical topics. Ellen is on Twitter as @Ellen_Friedman."

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Tackle two aspects of JavaScript development, modularity and ECMAScript 6 (ES6). With this practical guide, frontend and backend Node.js developers alike will learn how to scale out JavaScript applications by breaking codebases into smaller modules. Author Nicolas Bevacqua also covers features in ES6--the latest version of the specification that includes JavaScript--that support modularization. If you're a frontend developer or backend Node.js developer with a working knowledge of JavaScript, this book is for you. It's ideal for semi-senior developers, senior developers, technical leaders, and software architects.

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Have you ever felt frustrated working with someone else's code? Difficult-to-maintain source code is a big problem in software development today, leading to costly delays and defects. Be part of the solution. With this practical book, you'll learn 10 easy-to-follow guidelines for delivering C# software that's easy to maintain and adapt. These guidelines have been derived from analyzing hundreds of real-world systems. Written by consultants from the Software Improvement Group (SIG), this book provides clear and concise explanations, with advice for turning the guidelines into practice. Examples for this edition are written in C#, while our companion Java book provides clear examples in that language. Write short units of code: limit the length of methods and constructors Write simple units of code: limit the number of branch points per method Write code once, rather than risk copying buggy code Keep unit interfaces small by extracting parameters into objects Separate concerns to avoid building large classes Couple architecture components loosely Balance the number and size of top-level components in your code Keep your codebase as small as possible Automate tests for your codebase Write clean code, avoiding "code smells" that indicate deeper problems

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Can drinking coffee help people live longer? What makes a stock's price go up? Why did you get the flu? Causal questions like these arise on a regular basis, but most people likely have not thought deeply about how to answer them. This book helps you think about causality in a structured way: What is a cause, what are causes good for, and what is compelling evidence of causality? Author Samantha Kleinberg shows you how to develop a set of tools for thinking more critically about causes. You'll learn how to question claims, identify causes, make decisions based on causal information, and verify causes through further tests. Whether it's figuring out what data you need, or understanding that the way you collect and prepare data affects the conclusions you can draw from it, Why will help you sharpen your causal inference skills.

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Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering. Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples. You’ll examine: Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms Natural text techniques: bag-of-words, n-grams, and phrase detection Frequency-based filtering and feature scaling for eliminating uninformative features Encoding techniques of categorical variables, including feature hashing and bin-counting Model-based feature engineering with principal component analysis The concept of model stacking, using k-means as a featurization technique Image feature extraction with manual and deep-learning techniques

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If you're among the many hobbyists and designers who came to electronics through Arduino and Raspberry Pi, this cookbook will help you learn and apply the basics of electrical engineering without the need for an EE degree. Through a series of practical recipes, you'll learn how to solve specific problems while diving into as much or as little theory as you're comfortable with. Author Simon Monk (Raspberry Pi Cookbook) breaks down this complex subject into several topics, from using the right transistor to building and testing projects and prototypes. With this book, you can quickly search electronics topics and go straight to the recipe you need. It also serves as an ideal reference for experienced electronics makers. This cookbook includes: Theoretical concepts such as Ohm's law and the relationship between power, voltage, and current The fundamental use of resistors, capacitors and inductors, diodes, transistors and integrated circuits, and switches and relays Recipes on power, sensors and motors, integrated circuits, and radio frequency for designing electronic circuits and devices Advice on using Arduino and Raspberry Pi in electronics projects How to build and use tools, including multimeters, oscilloscopes, simulations software, and unsoldered prototypes

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If you want to push your Java skills to the next level, this book provides expert advice from Java leaders and practitioners. You'll be encouraged to look at problems in new ways, take broader responsibility for your work, stretch yourself by learning new techniques, and become as good at the entire craft of development as you possibly can Edited by Kevlin Henney and Trisha Gee, 97 Things Every Java Programmer Should Know reflects lifetimes of experience writing Java software and living with the process of software development. Great programmers share their collected wisdom to help you rethink Java practices, whether working with legacy code or incorporating changes since Java 8 A few of the 97 things you should know: "Behavior Is Easy, State Is Hard"-Edson Yanaga "Learn Java Idioms and Cache in Your Brain"-Jeanne Boyarsky "Java Programming from a JVM Performance Perspective"-Monica Beckwith "Garbage Collection Is Your Friend"-Holly K Cummins "Java's Unspeakable Types"-Ben Evans "The Rebirth of Java"-Sander Mak "Do You Know What Time It Is?"-Christin Gorman

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Dreamweaver CC is a powerful tool for designing all kinds of websites, from those with simple, static pages to interactive, media-driven sites for desktop, laptop, and mobile devices. But the program still doesn't include a printed guide to its amazing capabilities. That's where this Missing Manual comes in. With hands-on tutorials and coverage of every feature, you'll learn to build, deploy, and manage sites whether you're an experienced designer or just getting started. The important stuff you need to know: Dive into page design. Quickly learn the basics of working with text, images, links, and tables. Edit pages in Live view. Dynamically add elements to live pages and immediately see the results. Design once, and for all. Build fluid-grid sites that adapt themselves to desktop, tablet, and mobile devices. Troubleshoot your HTML. Use the new Element Quick View to reveal the hierarchy of page elements. Style with ease. Tap Dreamweaver's enhanced CSS Designer to copy and paste styles. Enhance Dreamweaver. Get new program features with add-ons that integrate directly with Dreamweaver. Bring your pages to life. Use jQuery UI to add interactive page elements like tabbed content panels. Create universal pages. Avoid browser incompatibility with workarounds.

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Take advantage of Chef's highly customizable design to tackle specific automation issues that you can't solve by simply using Chef's tools, resources, and services out of the box. With this practical guide, you'll examine the internal structure of this configuration management technology and learn where, how, and why to add custom code. Author Jon Cowie not only provides code snippets and practical advice for customizing Chef, but also helps you determine case by case whether it's in your best interests to customize at all. If you have intermediate-to-advanced Chef experience, this book is indispensable. * Explore Chef's typical setups and why you'd want to customize them* Learn the Ruby concepts needed to write customizations* Customize the Chef run process and explore Chef's internal classes* Gain more insight into your Chef runs through handlers and Chef's event stream* Level up your Chef recipes by writing your own resources and providers* Create and extend plugins for Knife--Chef's command-line tool* Interact with the Chef API to write scripts and reports* Learn how to contribute customizations to the Chef community

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