Search results for ""o'reilly media""

Cryptography, the science of secret writing, is the biggest, baddest security tool in the application programmer's arsenal. Cryptography provides three services that are crucial in secure programming. These include a cryptographic cipher that protects the secrecy of your data; cryptographic certificates, which prove identity (authentication); and digital signatures, which ensure your data has not been damaged or tampered with. This book covers cryptographic programming in Java. Java 1.1 and Java 1.2 provide extensive support for cryptography with an elegant architecture, the Java Cryptography Architecture (JCA). Another set of classes, the Java Cryptography Extension (JCE), provides additional cryptographic functionality. This book covers the JCA and the JCE from top to bottom, describing the use of the cryptographic classes as well as their innards. The book is designed for moderately experienced Java programmers who want to learn how to build cryptography into their applications. No prior knowledge of cryptography is assumed. The book is peppered with useful examples, ranging from simple demonstrations in the first chapter to full-blown applications in later chapters. Topics include: * The Java Cryptography Architecture (JCA) * The Java Cryptography Extension (JCE) * Cryptographic providers * The Sun key management tools * Message digests, digital signatures, and certificates (X509v3) * Block and stream ciphers * Implementations of the ElGamal signature and cipher algorithms * A network talk application that encrypts all data sent over the network * An email application that encrypts its messages Covers JDK 1.2 and JCE 1.2.

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There have been dozens of books on programming algorithms, but never before has there been one that uses Perl. Whether you are an amateur programmer or know a wide range of algorithms in other languages, this book will teach you how to carry out traditional programming tasks in a high-powered, efficient, easy-to-maintain manner with Perl. Topics range in complexity from sorting and searching to statistical algorithms, numerical analysis, and encryption.

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Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You'll understand why the tidymodels framework has been built to be used by a broad range of people.

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Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more

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Reactive systems and event-driven architecture are becoming indispensable to application design, and companies are taking note. Reactive systems ensure that applications are responsive, resilient, and elastic no matter what failures or errors may be occurring, while event-driven architecture offers a flexible and composable option for distributed systems. This practical book helps Java developers bring these approaches together using Quarkus 2.x, the Kubernetes-native Java framework. Clement Escoffier and Ken Finnigan show you how to take advantage of event-driven and reactive principles to build robust distributed systems, reducing latency and increasing throughput, particularly in microservices and serverless applications. You'll also get a foundation in Quarkus to help you create true Kubernetes-native applications for the cloud. Understand the fundamentals of reactive systems and event-driven architecture Learn how to use Quarkus to build reactive applications Combine Quarkus with Apache Kafka or AMQP to build reactive systems Develop microservices that utilize messages with Quarkus for use in event-driven architectures Learn how to integrate external messaging systems, such as Apache Kafka, with Quarkus Build applications with Quarkus using reactive systems and reactive programming concepts

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Get quick hands-on experience with Google Cloud. This cookbook provides a variety of self-contained recipes that show you how to use Google Cloud services for your enterprise application. Whether you're looking for practical ways to apply microservices, AI, analytics, security, or networking solutions, these recipes take you step-by-step through the process and provide discussions that explain how and why the recipes work. Ideal for system engineers and administrators, developers, network and database administrators, and data analysts, this cookbook helps you get started with Google Cloud regardless of your level of experience. Google veterans Rui Costa and Drew Hodun also cover advanced-level Google Cloud services for those who have appreciable experience with the platform. Learn how to get started with Google Cloud Understand the depth of services Google Cloud provides Gain hands-on experience using practical examples and labs Explore topics that include BigQuery, Cloud Run, and Kubernetes Build and run mobile and web applications on Google Cloud Examine ways to build your cloud applications for scale Build a minimum viable product (MVP) app to use in production Learn data platform and pipeline skills

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Data analytics may seem daunting, but if you're an experienced Excel user, you have a unique head start. With this hands-on guide, intermediate Excel users will gain a solid understanding of analytics and the data stack. By the time you complete this book, you'll be able to conduct exploratory data analysis and hypothesis testing using a programming language. Exploring and testing relationships are core to analytics. By using the tools and frameworks in this book, you'll be well positioned to continue learning more advanced data analysis techniques. Author George Mount, founder and CEO of Stringfest Analytics, demonstrates key statistical concepts with spreadsheets, then pivots your existing knowledge about data manipulation into R and Python programming. This practical book guides you through: Foundations of analytics in Excel: Use Excel to test relationships between variables and build compelling demonstrations of important concepts in statistics and analytics From Excel to R: Cleanly transfer what you've learned about working with data from Excel to R From Excel to Python: Learn how to pivot your Excel data chops into Python and conduct a complete data analysis

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Get up to speed with Helm, the preeminent package manager for the Kubernetes container orchestration system. This practical guide shows you how to efficiently create, install, and manage the applications running inside your containers. Helm maintainers Matt Butcher, Matt Farina, and Josh Dolitsky explain how this package manager fits into the Kubernetes ecosystem and provide an inside look at Helm's design and best practices. More than 70% of the organizations that work with Kubernetes use Helm today. While the Helm community provides thousands of packages, or charts, to help you get started, this book walks developers and DevOps engineers through the process of creating custom charts to package applications. If you have a working understanding of Kubernetes, you're ready to go. Explore primary features including frequently used Helm commands Learn how to build and deploy Helm charts from scratch Use Helm to manage complexity and achieve repeatable deployments Package an application and its dependencies for easy installation Manage the entire lifecycle of applications on Kubernetes Explore ways to extend Helm to add features and functionality Learn features for testing, handling dependencies, and providing security

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For programmers, analysts, and database administrators, this Nutshell guide is the essential reference for the SQL language used in today's most popular database products. This new fourth edition clearly documents SQL commands according to the latest ANSI/ISO standard and details how those commands are implemented in Microsoft SQL Server 2019 and Oracle 19c, as well as in the MySQL 8, MariaDB 10.5, and PostgreSQL 14 open source database products. You'll also get a concise overview of the relational database management system (RDBMS) model and a clear-cut explanation of foundational RDBMS concepts--all packed into a succinct, comprehensive, and easy-to-use format. Sections include: Background on the relational database model, including current and previous SQL standards Fundamental concepts necessary for understanding relational databases and SQL commands An alphabetical command reference to SQL statements, according to the SQL:2016 ANSI standard The implementation of each command by MySQL, Oracle, PostgreSQL, and SQL Server An alphabetical reference of the ANSI SQL:2016 functions and constructs as well as the vendor implementations Platform-specific functions unique to each implementation

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This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself. When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases. Understand best practices in TensorFlow model patterns and ML workflows Use code snippets as templates in building TensorFlow models and workflows Save development time by integrating prebuilt models in TensorFlow Hub Make informed design choices about data ingestion, training paradigms, model saving, and inferencing Address common scenarios such as model design style, data ingestion workflow, model training, and tuning

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Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. In each chapter, author Mahmoud Parsian shows you how to solve a data problem with a set of Spark transformations and algorithms. You'll learn how to tackle problems involving ETL, design patterns, machine learning algorithms, data partitioning, and genomics analysis. Each detailed recipe includes PySpark algorithms using the PySpark driver and shell script. With this book, you will: Learn how to select Spark transformations for optimized solutions Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions() Understand data partitioning for optimized queries Build and apply a model using PySpark design patterns Apply motif-finding algorithms to graph data Analyze graph data by using the GraphFrames API Apply PySpark algorithms to clinical and genomics data Learn how to use and apply feature engineering in ML algorithms Understand and use practical and pragmatic data design patterns

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Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models. You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies have pursued ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build. Get up to speed on the field of weak supervision, including ways to use it as part of the data science process Use Snorkel AI for weak supervision and data programming Get code examples for using Snorkel to label text and image datasets Use a weakly labeled dataset for text and image classification Learn practical considerations for using Snorkel with large datasets and using Spark clusters to scale labeling

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Software development today is embracing events and streaming data, which optimizes not only how technology interacts but also how businesses integrate with one another to meet customer needs. This phenomenon, called flow, consists of patterns and standards that determine which activity and related data is communicated between parties over the internet. This book explores critical implications of that evolution: What happens when events and data streams help you discover new activity sources to enhance existing businesses or drive new markets? What technologies and architectural patterns can position your company for opportunities enabled by flow? James Urquhart, global field CTO at VMware, guides enterprise architects, software developers, and product managers through the process. Learn the benefits of flow dynamics when businesses, governments, and other institutions integrate via events and data streams Understand the value chain for flow integration through Wardley mapping visualization and promise theory modeling Walk through basic concepts behind today's event-driven systems marketplace Learn how today's integration patterns will influence the real-time events flow in the future Explore why companies should architect and build software today to take advantage of flow in coming years

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Understand the Blockchain Opportunity: No Technical Background Required. Remember thedawn of the internet? The advent of mobile and social media? Yet another digital revolution is nowunderway. Like its predecessors, blockchains are about to transform the way we live, work, and play, while disrupting entrenched industries and shattering conventional business models.Move past the hype and equip yourself to forecast how blockchains will change our world and impactyou and your business. Author Alison McCauley helps non-technical executives to understandhow this technology will trigger change, shift the balance of power, and bring competitiveadvantage to those who know how to leverage them.Unblocked explains: Why ignoring this technology exposes you to competitive disruption What this new technology revolution embraces--no technical background required How to prepare your organization to respond to the coming shift

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Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order. This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly. Extract data from APIs and web pages Prepare textual data for statistical analysis and machine learning Use machine learning for classification, topic modeling, and summarization Explain AI models and classification results Explore and visualize semantic similarities with word embeddings Identify customer sentiment in product reviews Create a knowledge graph based on named entities and their relations

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Developing applications for the Android mobile operating system can seem daunting, particularly if it requires learning a new programming language: Kotlin, now Android's official development language. With this practical book, Android developers will learn how to make the transition from Java to Kotlin, including how Kotlin provides a true advantage for gaining control over asynchronous computations. Authors Pierre-Olivier Laurence, Amanda Hinchman-Dominguez, G. Blake Meike, and Mike Dunn explore implementations of the most common tasks in native Android development, and show you how Kotlin can help you solve concurrency problems. With a focus on structured concurrency, a new asynchronous programming paradigm, this book will guide you through one of Kotlin's most powerful constructs, coroutines. Learn about Kotlin essentials and the Kotlin Collections Framework Explore Android fundamentals: the operating system and the application container and its components Learn about thread safety and how to handle concurrency Write sequential, asynchronous work at a low cost Examine structured concurrency with coroutines, and learn how channels make coroutines communicate Learn how to use flows for asynchronous data processing Understand performance considerations using Android profiling tools Use performance optimizations to trim resource consumption

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Why is PHP the most widely used programming language on the web? This updated edition teaches everything you need to know to create effective web applications using the latest features in PHP 7.4. You’ll start with the big picture and then dive into language syntax, programming techniques, and other details, using examples that illustrate both correct usage and common idioms. If you have a working knowledge of HTML, authors Kevin Tatroe and Peter MacIntyre provide many style tips and practical programming advice in a clear and concise manner to help you become a top-notch PHP programmer. Understand what’s possible when you use PHP programs Learn language fundamentals, including data types, variables, operators, and flow control statements Explore functions, strings, arrays, and objects Apply common web application techniques, such as form processing, data validation, session tracking, and cookies Interact with relational databases like MySQL or NoSQL databases such as MongoDB Generate dynamic images, create PDF files, and parse XML files Learn secure scripts, error handling, performance tuning, and other advanced topics Get a quick reference to PHP core functions and standard extensions

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Serverless computing is radically changing the way we build and deploy applications. With cloud providers running servers and managing machine resources, companies now can focus solely on the application's business logic and functionality. This hands-on book shows experienced programmers how to build and deploy scalable machine learning and deep learning models using serverless architectures with Microsoft Azure. You'll learn step-by-step how to code machine learning into your projects using Python and pre-trained models that include tools such as image recognition, speech recognition, and classification. You'll also examine issues around deployment and continuous delivery including scaling, security, and monitoring. This book is divided into four parts: Cloud-based development: learn the basics of serverless computing with machine learning, functions as a service (FaaS), and the use of APIs Adding intelligence: create serverless applications using Azure Functions; learn how to use pre-built machine-learning and deep-learning models Deployment and continuous delivery: get up to speed with Azure Kubernetes Service, as well as Azure Security Center, and Azure Monitoring Application examples: deliver data at the edge, build conversational interfaces, and use convolutional neural networks for image classification

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Threat modeling is one of the most essential--and most misunderstood--parts of the development lifecycle. Whether you're a security practitioner or a member of a development team, this book will help you gain a better understanding of how you can apply core threat modeling concepts to your practice to protect your systems against threats. Contrary to popular belief, threat modeling doesn't require advanced security knowledge to initiate or a Herculean effort to sustain. But it is critical for spotting and addressing potential concerns in a cost-effective way before the code's written--and before it's too late to find a solution. Authors Izar Tarandach and Matthew Coles walk you through various ways to approach and execute threat modeling in your organization. Explore fundamental properties and mechanisms for securing data and system functionality Understand the relationship between security, privacy, and safety Identify key characteristics for assessing system security Get an in-depth review of popular and specialized techniques for modeling and analyzing your systems View the future of threat modeling and Agile development methodologies, including DevOps automation Find answers to frequently asked questions, including how to avoid common threat modeling pitfalls

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Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems.Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniques

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Why reinvent the wheel every time you run into a problem with JavaScript? This cookbook is chock-full of code recipes for common programming tasks, along with techniques for building apps that work in any browser. You'll get adaptable code samples that you can add to almost any project--and you'll learn more about JavaScript in the process. The recipes in this book take advantage of the latest features in ECMAScript 2020 and beyond and use modern JavaScript coding standards. You'll learn how to: Set up a productive development environment with a code editor, linter, and test server Work with JavaScript data types, such as strings, arrays, and BigInts Improve your understanding of JavaScript functions, including arrow functions, closures, and generators Apply object-oriented programming concepts like classes and inheritance Work with rich media in JavaScript, including audio, video, and SVGs Manipulate HTML markup and CSS styles Use JavaScript anywhere with Node.js Access and manipulate remote data with REST, GraphQL, and Fetch Get started with the popular Express application-building framework Perform asynchronous operations with Promises, async/await, and web workers

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If you’re looking to develop native applications in Kubernetes, this is your guide. Developers and AppOps administrators will learn how to build Kubernetes-native applications that interact directly with the API server to query or update the state of resources. AWS developer advocate Michael Hausenblas and Red Hat principal software engineer Stefan Schimanski explain the characteristics of these apps and show you how to program Kubernetes to build them. You’ll explore the basic building blocks of Kubernetes, including the client-go API library and custom resources. All you need to get started is a rudimentary understanding of development and system administration tools and practices, such as package management, the Go programming language, and Git. Walk through Kubernetes API basics and dive into the server’s inner structure Explore Kubernetes’s programming interface in Go, including Kubernetes API objects Learn about custom resources—the central extension tools used in the Kubernetes ecosystem Use tags to control Kubernetes code generators for custom resources Write custom controllers and operators and make them production ready Extend the Kubernetes API surface by implementing a custom API server

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Web 2.0 makes headlines, but how does it make money? This concise guide explains what's different about Web 2.0 and how those differences can improve your company's bottom line. Whether you're an executive plotting the next move, a small business owner looking to expand, or an entrepreneur planning a startup, Web 2.0: A Strategy Guide illustrates through real-life examples how businesses, large and small, are creating new opportunities on today's Web. This book is about strategy. Rather than focus on the technology, the examples concentrate on its effect. You will learn that creating a Web 2.0 business, or integrating Web 2.0 strategies with your existing business, means creating places online where people like to come together to share what they think, see, and do. When people come together over the Web, the result can be much more than the sum of the parts. The customers themselves help build the site, as old-fashioned "word of mouth" becomes hypergrowth. Web 2.0: A Strategy Guide demonstrates the power of this new paradigm by examining how: Flickr, a classic user-driven business, created value for itself by helping users create their own value Google made money with a model based on free search, and changed the rules for doing business on the Web-opening opportunities you can take advantage of Social network effects can support a business-ever wonder how FaceBook grew so quickly? Businesses like Amazon tap into the Web as a source of indirect revenue, using creative new approaches to monetize the investments they've made in the Web

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Take the next steps toward mastering deep learning, the machine learning method that’s transforming the world around us by the second. In this practical book, you’ll get up to speed on key ideas using Facebook’s open source PyTorch framework and gain the latest skills you need to create your very own neural networks. Ian Pointer shows you how to set up PyTorch on a cloud-based environment, then walks you through the creation of neural architectures that facilitate operations on images, sound, text, and more through deep dives into each element. He also covers the critical concepts of applying transfer learning to images, debugging models, and PyTorch in production. Learn how to deploy deep learning models to production Explore PyTorch use cases from several leading companies Learn how to apply transfer learning to images Apply cutting-edge NLP techniques using a model trained on Wikipedia Use PyTorch’s torchaudio library to classify audio data with a convolutional-based model Debug PyTorch models using TensorBoard and flame graphs Deploy PyTorch applications in production in Docker containers and Kubernetes clusters running on Google Cloud

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Companies from startups to corporate giants face massive amounts of disruption today. Now more than ever, organizations need nimble and responsive leaders who know how to exploit the opportunities that change brings. In this insightful book, Jean Dahl, a senior executive and expert in the Lean mindset and its methods, demonstrates why you need to embrace Modern Lean principles and thinking to redefine leadership in this age of digital disruption in order to continuously evolve the Lean enterprise. Drawing on nearly three decades of corporate and consulting experience, Ms. Dahl lays out a new holistic framework for developing Modern Lean leaders. Through personal experiences and compelling real-world case studies, she explains specific steps necessary for you and your company to proactively understand and respond to change. Understand the leadership challenges Lean leaders face in our 21st century global economy Explore the six dimensions of the Modern Lean Framework™ Learn and apply the nine steps necessary to become a Lean leader Use Modern Lean methods to build a culture of continuous learning that can be sustained and maintained within your organization Seize competitive advantage by embracing Modern Lean to tbuild an enterprise that understands how to respond to disruption

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Big Data Solution Architecture provides everyone from CIOs and COOs to lead architects and lead developers with the fundamental concepts of big data development. Authors Ted Malaska and Jonathan Seidman guide you through all the major components necessary to start, architect, and develop successful big data projects. This practical book covers a variety of different big data architectures and applications, from massive data pipelines to web scale applications. Each chapter addresses a different part of the software development life cycle and identifies patterns that build on one another to maximize success throughout the life of your project. You’ll learn how to: Build a Big Data center of excellence in your company for the first time Identify and manage risk in your data project Retain and motivate teams to increase engagement and innovation Maximize Big Data ROI and align cost structure to help your company attain success

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Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you’ll learn how to build features that use powerful AI features to identify images, make predictions, generate content, recommend things, and more. AI is increasingly essential for every developer—and you don’t need to be a data scientist or mathematician to take advantage of it in your apps. Explore Swift-based AI and ML techniques for building applications. Learn where and how AI-driven features make sense. Inspect tools such as Apple’s Python-powered Turi Create and Google’s Swift for TensorFlow to train and build models. I: Fundamentals and Tools—Learn AI basics, our task-based approach, and discover how to build or find a dataset. II: Task Based AI—Build vision, audio, text, motion, and augmentation-related features; learn how to convert preexisting models. III: Beyond—Discover the theory behind task-based practice, explore AI and ML methods, and learn how you can build it all from scratch... if you want to

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As more companies move toward microservices and other distributed technologies, the complexity of these systems increases. You can't remove the complexity, but through Chaos Engineering you can discover vulnerabilities and prevent outages before they impact your customers. This practical guide shows engineers how to navigate complex systems while optimizing to meet business goals. Two of the field's prominent figures, Casey Rosenthal and Nora Jones, pioneered the discipline while working together at Netflix. In this book, they expound on the what, how, and why of Chaos Engineering while facilitating a conversation from practitioners across industries. Many chapters are written by contributing authors to widen the perspective across verticals within (and beyond) the software industry. Learn how Chaos Engineering enables your organization to navigate complexity Explore a methodology to avoid failures within your application, network, and infrastructure Move from theory to practice through real-world stories from industry experts at Google, Microsoft, Slack, and LinkedIn, among others Establish a framework for thinking about complexity within software systems Design a Chaos Engineering program around game days and move toward highly targeted, automated experiments Learn how to design continuous collaborative chaos experiments

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Why is GraphQL the most innovative technology for fetching data since Ajax? By providing a query language for your APIs and a runtime for fulfilling queries with your data, GraphQL presents a clear alternative to REST and ad hoc web service architectures. With this practical guide, Alex Banks and Eve Porcello deliver a clear learning path for frontend web developers, backend engineers, and project and product managers looking to get started with GraphQL. You’ll explore graph theory, the graph data structure, and GraphQL types before learning hands-on how to build a schema for a photo-sharing application. This book also introduces you to Apollo Client, a popular framework you can use to connect GraphQL to your user interface. Explore graph theory and review popular graph examples in use today Learn how GraphQL applies database querying methods to the internet Create a schema for a PhotoShare application that serves as a roadmap and a contract between the frontend and backend teams Use JavaScript to build a fully functioning GraphQL service and Apollo to implement a client Learn how to prepare GraphQL APIs and clients for production

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Tackling an app development project on multiple platforms is usually an arduous task, but with React Native, you can build cross-platform mobile apps that look and behave just like native apps built with Swift or Java. If you’re familiar with JavaScript, the recipes in this cookbook will help you understand the React Native ecosystem, deal with design and hardware issues, take on the deployment process, and write maintainable code. How do you organize a project? Or design an app that can access a device’s camera? Based on author Jonathan Lebensold’s personal journey through the app development process, the recipes in this cookbook will not only provide you with quick answers, they can also inspire you to come up with your own solutions. Examine the software tools you’ll use to build a React Native app Leverage components and JavaScript libraries in the React ecosystem Design cross-platform apps that balance UX, platform conventions, and technical complexity Get common use cases and advice for taking advantage of device hardware Automate app publishing, share your iOS App with beta testers, and configure app settings Learn strategies for ensuring your code is well factored, easily maintained, and correct

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Dive into Swift 4.x, the latest version of Apple's easy-to-use programming language for macOS, iOS, watchOS, and tvOS. With this practical guide, you'll quickly get up to speed on language basics and then use Swift to build three complete apps, all tightly linked together: an iOS note-taking app, its OSX counterpart that uses iCloud to sync data, and an app for the Apple Watch that makes the user’s data available at a moment's notice. You’ll learn not only how to write code in Swift, but also why Swift works the way that it does, and how to build upon its foundations. Then you’ll explore Swift in the wider world, including open-source frameworks that your apps can use, how to use app extensions make your app play nice with other apps, and how to take Swift beyond Apple’s domain with open-source Swift tools.

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From Facebook Messenger to Kik, and from Slack bots to Google Assistant, Amazon Alexa, and email bots, the new conversational apps are revolutionizing the way we interact with software. This practical guide shows you how to design and build great conversational experiences and delightful bots that help people be more productive, whether it's for a new consumer service or an enterprise efficiency product.Ideal for designers, product managers, and entrepreneurs, this book explores what works and what doesn't in real-world bot examples, and provides practical design patterns for your bot-building toolbox. You'll learn how to use an effective onboarding process, outline different flows, define a bot personality, and choose the right balance of rich control and text.Explore different bot use-cases and design best practicesUnderstand bot anatomy-such as brand and personality, conversations, advanced UI controls-and their associated design patternsLearn steps for building a Facebook Messenger consumer bot and a Slack business botExplore the lessons learned and shared experiences of designers and entrepreneurs who have built botsDesign and prototype your first bot, and experiment with user feedback

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Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems

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Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you’ll first start to learn with regression modelling and then move into more advanced topics such as neural networks and tree-based methods. Finally, you’ll delve into the frontier of machine learning, using the caret package in R. Once you develop a familiarity with topics such as the difference between regression and classification models, you’ll be able to solve an array of machine learning problems. Author Scott V. Burger provides several examples to help you build a working knowledge of machine learning. Explore machine learning models, algorithms, and data training Understand machine learning algorithms for supervised and unsupervised cases Examine statistical concepts for designing data for use in models Dive into linear regression models used in business and science Use single-layer and multilayer neural networks for calculating outcomes Look at how tree-based models work, including popular decision trees Get a comprehensive view of the machine learning ecosystem in R Explore the powerhouse of tools available in R’s caret package

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In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming. You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—including classification, clustering, collaborative filtering, and anomaly detection—to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you’ll find the book’s patterns useful for working on your own data applications. With this book, you will: Familiarize yourself with the Spark programming model Become comfortable within the Spark ecosystem Learn general approaches in data science Examine complete implementations that analyze large public data sets Discover which machine learning tools make sense for particular problems Acquire code that can be adapted to many uses

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For system administrators, programmers, and end users, shell command or carefully crafted shell script can save you time and effort, or facilitate consistency and repeatability for a variety of common tasks. This cookbook provides more than 300 practical recipes for using bash, the popular Unix shell that enables you to harness and customize the power of any Unix or Linux system. Ideal for new and experienced users alike—including proficient Windows users and sysadmins—this updated second edition helps you solve a wide range of problems. You’ll learn ways to handle input/output, file manipulation, program execution, administrative tasks, and many other challenges. Each recipe includes one or more scripting examples and a discussion of why the solution works. You’ll find recipes for problems including: Standard output and input, and executing commands Shell variables, shell logic, and arithmetic Intermediate shell tools and advanced scripting Searching for files with find, locate, and slocate Working with dates and times Creating shell scripts for various end-user tasks Working with tasks that require parsing Writing secure shell scripts Configuring and customizing bash

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Traditional intrusion detection and logfile analysis are no longer enough to protect today’s complex networks. In the updated second edition of this practical guide, security researcher Michael Collins shows InfoSec personnel the latest techniques and tools for collecting and analyzing network traffic datasets. You’ll understand how your network is used, and what actions are necessary to harden and defend the systems within it. In three sections, this book examines the process of collecting and organizing data, various tools for analysis, and several different analytic scenarios and techniques. New chapters focus on active monitoring and traffic manipulation, insider threat detection, data mining, regression and machine learning, and other topics. You’ll learn how to: Use sensors to collect network, service, host, and active domain data Work with the SiLK toolset, Python, and other tools and techniques for manipulating data you collect Detect unusual phenomena through exploratory data analysis (EDA), using visualization and mathematical techniques Analyze text data, traffic behavior, and communications mistakes Identify significant structures in your network with graph analysis Examine insider threat data and acquire threat intelligence Map your network and identify significant hosts within it Work with operations to develop defenses and analysis techniques

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Investors recognize that technology is a powerful tool for obtaining and interpreting financial data that could give them the one thing everyone on Wall Street wants: an edge. Yet, many don’t realize that you don’t need to be a programmer to access behind-the-scenes financial information from Bloomberg, IHS Markit, or other systems found at most banks and investment firms. This practical guide teaches analysts a useful subset of Excel skills that will enable them to access and interpret financial information—without any prior programming experience. This book will show analysts, step-by-step, how to quickly produce professional reports that combine their views with Bloomberg or Markit data including historical financials, comparative analysis, and relative value. For portfolio managers, this book demonstrates how to create professional summary reports that contain a high-level view of a portfolio’s performance, growth, risk-adjusted return, and composition. If you are a programmer, this book also contains a parallel path that covers the same topics using C#. Topics include: Access additional data that isn’t visible on Bloomberg screens Create tables containing corporate data that makes it possible to compare multiple companies, bonds, or loans side-by- side Build one-page analytic (“Tear Sheet”) reports for individual companies that incorporates important financials, custom notes, relative value comparison of the company to its peers, and price trends with research analyst targets Build two-page portfolio summary report that contains a high-level view of the portfolio’s performance, growth, risk-adjusted return, and composition Explore daily prices and facility information for most of the tradable corporate bond and loan market Determine the relationship between two securities (or index) using correlation and regression Compare each security’s performance to a cohort made of up of securities with similar risk and return characteristics Measure portfolio risk-adjusted return by calculating variance, standard deviation, and Sharpe ratio Use Markit data to identify meaningful trends in prices, new issue spreads, and refinancings

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There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You’ll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into: Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability

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What will you learn from this book? It’s no secret the world around you is becoming more connected, more configurable, more programmable, more computational. You can remain a passive participant, or you can learn to code. With Head First Learn to Code you’ll learn how to think computationally and how to write code to make your computer, mobile device, or anything with a CPU do things for you. Using the Python programming language, you’ll learn step by step the core concepts of programming as well as many fundamental topics from computer science, such as data structures, storage, abstraction, recursion, and modularity. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Learn to Code 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 multi-sensory learning experience is designed for the way your brain really works.

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Although web components are still on the bleeding edge-barely supported in modern browsers-the technology is also moving extremely fast. This practical guide gets you up to speed on the concepts underlying W3C's emerging standard and shows you how to build custom, reusable HTML5 Web Components. Regardless of your experience with libraries such as jQuery and Polymer, this book teaches JavaScript developers the DOM manipulations these libraries perform. You'll learn how to build a basic widget with vanilla JavaScript and then convert it into a web component that's semantic, declarative, encapsulated, consumable, and maintainable. With custom components, the Web can finally fulfill its potential as a natively extensible application platform. This book gets you in at the right time. Understand core concepts (such as normal flow and positioning, and Z-index) for properly positioning, dragging, and resizing elements Explore UI concepts and patterns typically abstracted away by Dojo, jQuery UI, Kendo UI, and other libraries Dive into the W3C standard and convert your working widget example into a fully functioning web component Learn how to encapsulate, package, and deploy your web components with Google's Polymer framework

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If your organization is about to enter the world of big data, you not only need to decide whether Apache Hadoop is the right platform to use, but also which of its many components are best suited to your task. This field guide makes the exercise manageable by breaking down the Hadoop ecosystem into short, digestible sections. You'll quickly understand how Hadoop's projects, subprojects, and related technologies work together. Each chapter introduces a different topic-such as core technologies or data transfer-and explains why certain components may or may not be useful for particular needs. When it comes to data, Hadoop is a whole new ballgame, but with this handy reference, you'll have a good grasp of the playing field. Topics include: Core technologies-Hadoop Distributed File System (HDFS), MapReduce, YARN, and Spark Database and data management-Cassandra, HBase, MongoDB, and Hive Serialization-Avro, JSON, and Parquet Management and monitoring-Puppet, Chef, Zookeeper, and Oozie Analytic helpers-Pig, Mahout, and MLLib Data transfer-Scoop, Flume, distcp, and Storm Security, access control, auditing-Sentry, Kerberos, and Knox Cloud computing and virtualization-Serengeti, Docker, and Whirr

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What's the best way to develop for a Web gone wild? That's easy. Simply scrap the rules you've relied on all these years and embrace uncertainty as a core tenet of design. In this practical book, veteran developer Rob Larsen outlines the principles out what he calls The Uncertain Web, and shows you techniques necessary to successfully make the transition. By combining web standards, progressive enhancement, an iterative approach to design and development, and a desire to question the status quo, your team can create sites and applications that will perform well in a wide range of present and future devices. This guide points the way. Topics include: Navigating thousands of browser/device/OS combinations Focusing on optimal, not absolute solutions Feature detection, Modernizr, and polyfills RWD, mobile first, and progressive enhancement UIs that work with multiple user input modes Image optimization, SVG, and server-side options The horribly complex world of web video The Web we want to see in the future

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If you're getting started with iOS development, or want a firmer grasp of the basics, this practical guide provides a clear view of its fundamental building blocks - Objective-C, Xcode, and Cocoa Touch. You'll learn object-oriented concepts, understand how to use Apple's development tools, and discover how Cocoa provides the underlying functionality iOS apps need to have. Dozens of example projects are available at GitHub. Once you master the fundamentals, you'll be ready to tackle the details of iOS app development with author Matt Neuburg's companion guide, Programming iOS 7 - coming in December 2013. Explore the C language to learn how Objective-C works Learn how instances are created, and why they're so important Tour the lifecycle of an Xcode project, from inception to App Store Discover how to build interfaces with nibs and the nib editor Explore Cocoa's use of Objective-C linguistic features Use Cocoa's event-driven model and major design patterns Learn the role of accessors, key-value coding, and properties Understand the power of ARC-based object memory management Send messages and data between Cocoa objects

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SVG is extremely powerful, with its reduced HTTP requests and crispness on any display. It becomes increasingly more interesting as you explore its capabilities for responsive animation and performance boons. When you animate SVG, you must be aware of normal image traits like composition, color, implementation, and optimization. But when you animate, it increases the complexity of each of these factors exponentially. This practical book takes a deep dive into how you can to solve these problems with stability, performance, and creativity in mind. Learn how to make SVG cross-browser compatible, backwards compatible, optimized, and responsive Plan and debug animation Make a complex animation responsive, as many sites are responsive Profile each animation technique in terms of performance so that you know what you're getting in to with each library or native technology

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Now may be the perfect time to enter the wearables industry. With the range of products that have appeared in recent years, you can determine which ideas resonate with users and which don't before leaping into the market. In this practical guide, author Scott Sullivan examines the current wearables ecosystem and then demonstrates the impact that service design in particular will have on these types of devices going forward. You'll learn about the history and influence of activity trackers, smartwatches, wearable cameras, the controversial Google Glass experiment, and other devices that have come out of the recent Wild West period. This book also dives into many other aspects of wearables design, including tools for creating new products and methodologies for measuring their usefulness. You'll explore: Emerging types of wearable technologies How to design services around wearable devices Key concepts that govern service design Prototyping processes and tools such as Arduino and Processing The importance of storytelling for introducing new wearables How wearables will change our relationship with computers

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A key task that any aspiring data-driven organization needs to learn is data wrangling, the process of converting raw data into something truly useful. This practical guide provides business analysts with an overview of various data wrangling techniques and tools, and puts the practice of data wrangling into context by asking, "What are you trying to do and why?" Wrangling data consumes roughly 50-80% of an analyst's time before any kind of analysis is possible. Written by key executives at Trifacta, this book walks you through the wrangling process by exploring several factors-time, granularity, scope, and structure-that you need to consider as you begin to work with data. You'll learn a shared language and a comprehensive understanding of data wrangling, with an emphasis on recent agile analytic processes used by many of today's data-driven organizations. Appreciate the importance-and the satisfaction-of wrangling data the right way. Understand what kind of data is available Choose which data to use and at what level of detail Meaningfully combine multiple sources of data Decide how to distill the results to a size and shape that can drive downstream analysis

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Pixels use electricity, and a lot of it. If the Internet were a country, it would be the sixth largest in terms of electricity use. That's because today's average web page has surpassed two megabytes in size, leading to slow load times, frustrated users, and a lot of wasted energy. With this practical guide, your web design team will learn how to apply sustainability principles for creating speedy, user-friendly, and energy-efficient digital products and services. Author Tim Frick introduces a web design framework that focuses on four key areas where these principles can make a difference: content strategy, performance optimization, design and user experience, and green hosting. You'll discover how to provide users with a streamlined experience, while reducing the environmental impact of your products and services. Learn why 90% of the data that ever existed was created in the last year Use sustainability principles to innovate, reduce waste, and function more efficiently Explore green hosting, sustainable business practices, and lean/agile workflows Put the right things in front of users at precisely the moment they need them-and nothing more Increase site search engine visibility, streamline user experience, and make streaming video more efficient Use Action Items to explore concepts outlined in each chapter

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