Search results for ""manning publications""

DESCRIPTION Wanting mobile apps to run on iOS, Android, and Windows Phone doesn't mean having to write them in three different languages. Apache Cordova provides a common set of APIs to access native device functionality such as the file system, camera, and contacts from apps written in HTML, CSS and Javascript, along with a command line tool to produce the binaries required for multiple mobile platforms. Apache Cordova in Action simplifies the entire process of creating and launching hybrid mobile apps using Cordova or Phonegap. By following carefully selected examples, step by step tutorials, and crystal-clear explanations, readers will learn to build apps from the Cordova CLI and make use of device features like the camera and accelerometer. For those just learning to design mobile apps, the book discusses ways to build mobile friendly, professional-quality UI and UX. Finally, the book covers testing techniques and explains the PhoneGap Build service, along with how to submit applications to Google Play and the Apple App Store. KEY SELLING POINTS Step by step tutorials Crystal clear explanations Simplifies the entire process of app development AUDIENCE Readers need to be familiar with HTML, CSS, and JavaScript. No prior experience with mobile app development is required. ABOUT THE TECHNOLOGY Cordova boasts a vibrant open source plugin ecosystem providing hooks into multiple device features and adding support for multiple different types of applications. Better still, when using Cordova with UI frameworks like jQuery Mobile, Ionic, or Sencha Touch, users can deploy their HTML based apps as native applications on any mobile device.

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It’s tedious and time-consuming to create OS-specific versions of every desktop application, especially with different set of tools for each platform. NW.js radically simplifies desktop development, providing a true cross-platform development stack built on HTML, CSS and JavaScript, Node.js modules, and the Chrome Blink engine. NW.js applications interact with the host operating system just like any other platform-native project, so developers have full access to all local files and resources. The performance is great, and best of all, it saves developers time because they only have to write one version of their application. Cross-Platform Desktop Applications guides readers step-by-step as they learn to develop NW.js desktop applications that run on Windows, OSX and Linux. They begin by getting the big picture of what NW.js can (and can’t) do. Readers test drive NW.js as they build their first desktop application. Next, they find out how to take advantage of OSspecific features like menus, system-tray apps, clipboards, and the file system. Along the way, this book teaches how to debug errors and diagnose performance bottlenecks with NW.js’s browser developer tools, package an application as a standalone executable for each OS, and even distribute it to various app stores. The book gives developers the inspiration and skills they need to code pro quality desktop applications using the web languages they already know. Key features: Step-by-step lessons Package and distribute application to a variety of app stores Develop pro quality desktop applications with web languages AUDIENCE Written for web designers and developers familiar with HTML, CSS, and JavaScript. No desktop app development experience required. ABOUT THE TECHNOLOGY NW.js radically simplifies desktop development, providing a true crossplatform development stack built on HTML, CSS and JavaScript, Node.js modules, and the Chrome Blink engine.

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According to Apple, there are currently 380,000 registered iOS developers and over a billion iOS devices in use worldwide. Swift, the language of iOS development, is the fastest growing programming language. iOS Development with Swift is a hands-on guide to creating apps for iPhone and iPad using the Swift language. It starts by giving a birdseye view of how an iOS application works and what it takes to build one. With the basics well in hand, the book takes readers through progressively more challenging examples as they learn how to design iOS apps, build good layouts, handle navigation, and interact with the device’s camera. Key Features: · Hands-on guide to creating apps · Teaches the very basics · Rich in examples Written for readers with experience using a language like Java, Python, or C#. No prior iOS development or Swift experience required. About the Technology: Swift is a modern language created by Apple. In 2015 Swift was rated the most loved programming language on Stack Overflow, and it is currently ranked 17 in the programming language rankings guide of January 2016.

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In the future, there are going to be millions of jobs with no one to fill them if more kids don't learn how to code. So why aren't more kids learning to program? Some think it's too hard, and others don't have parents who can help them because they don't know programming themselves. Learning to code with a tool like Scratch, an open source programming platform maintained by MIT, and having fun goals, like writing games, just might make a difference. That's where this book comes in. Hello, Scratch! is a how-to book that helps parents and kids work together to learn programming skills by creating new versions of old retro-style arcade games with Scratch. By building games, readers not only create fun finished products, but they'll learn important programming skills along the way. By the time readers are done, they'll be able to create their own games and understand the basics of computer programming and game design. Key Features: · Introduction to Scratch · Easy to follow examples · Step-by-step guide This book is for kids and their parents who want to learn to program while creating games. No programming experience needed! About the Technology: Scratch is a drag-and-drop programming language created by the college Massachusetts Institute of Technology (MIT). What can you make with Scratch? The short answer is anything.

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DESCRIPTION Being able to make near-real-time decisions is becoming increasingly crucial. To succeed, we need machine learning systems that can turn massive amounts of data into valuable insights. But when you're just starting out in the data science field, how do you get started creating machine learning applications? The answer is TensorFlow, a new open source machine learning library from Google. The TensorFlow library can take your high level designs and turn them into the low level mathematical operations required by machine learning algorithms. Machine Learning with TensorFlow teaches readers about machine learning algorithms and how to implement solutions with TensorFlow. It starts with an overview of machine learning concepts and moves on to the essentials needed to begin using TensorFlow. Each chapter zooms into a prominent example of machine learning. Readers can cover them all to master the basics or skip around to cater to their needs. By the end of this book, readers will be able to solve classification, clustering, regression, and prediction problems in the real world. KEY FEATURES • Lots of diagrams, code examples, and exercises • Solves real-world problems with TensorFlow • Uses well-studied neural network architectures • Presents code that can be used for the readers’ own applications AUDIENCE This book is for programmers who have some experience with Python and linear algebra concepts like vectors and matrices. No experience with machine learning is necessary. ABOUT THE TECHNOLOGY Google open-sourced their machine learning framework called TensorFlow in late 2015 under the Apache 2.0 license. Before that, it was used proprietarily by Google in its speech recognition, Search, Photos, and Gmail, among other applications. TensorFlow is one the most popular machine learning libraries.

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DESCRIPTION The Oculus Rift is an exciting next generation VR headset developed by OculusVR. Whether it's in a game, an architectural walk-through, or a teaching simulation, the goal of any immersive virtual reality experience is to make users feel like they're in the middle of the action. With precise, high-quality optics and a flexible programmatic interface, the Rift provides real-life field of view and head tracking hardware for natural interaction that finally nails the feeling of being there. Oculus Rift in Action introduces the powerful Oculus Rift headset and shows how to integrate its many features into 3D games and other virtual reality experiences. First, it discusses the capabilities of the Rift hardware. Then, it provides interesting and instantly-relevant examples that walk readers through programming real applications using the Oculus SDK. Along the way, the book offers practical guidance on using the Rift's sensors to produce a natural, fluid, immersive 3D experience; readers will be ready to hit the ground running with the first VR killer app when the consumer Rift is released! RETAIL SELLING POINTS An in depth guide for creating immersive VR experiences Shows the right way to create compelling VR applications Plenty of useful examples with detailed instructions AUDIENCE Readers can use this book even if they don't yet own the Oculus Rift hardware. Some experience with C++ or another OO language is required for the programming examples. No previous knowledge of optics, display, or motion tracking is expected. ABOUT THE TECHNOLOGY The Oculus Rift is a VR headset with a field comparable to what you'd get if you surrounded yourself with an array of a dozen monitors. Combined with the wide field of view, it includes head-tracking hardware so that when you turn your head, the view automatically changes, creating a feeling of 'really being there'.

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Master Java persistence using the industry-leading tools Spring Data and Hibernate. In Java Persistence with Spring Data and Hibernate you will learn: Mapping persistent classes, value types, and inheritance Mapping collections and entity associations Processing transactions with Spring Data and Hibernate Creating fetch plans, strategies, and profiles Filtering data Building Spring Data REST projects Using Java persistence with non-relational databases Querying JPA with QueryDSL Testing Java persistence applications Java Persistence with Spring Data and Hibernate teaches you the ins-and-outs of Java persistence with hands-on examples using Spring Data, JPA and Hibernate. The book carefully analyzes the capabilities of the major Java persistence tools, and guides you through the most common use cases. You'll learn how to make and utilize mapping strategies, and efficiently test Java persistence applications. The practical techniques are demonstrated with both relational and non-relational databases. about the technology Persistence enables an application's data to exist for the long term, even after a program is stopped or terminated. Whether you're saving state from session to session or maintaining long-term records, Java persistence tools like Spring Data, JPA, and Hibernate help deliver the object relational mapping that connects code's objects with your database. about the book Java Persistence with Spring Data and Hibernate explores persistence with the most popular available tools. You'll benefit from detailed coverage of Spring Data JPA, Spring Data JDBC, Spring Data REST, JPA, and Hibernate, comparing and contrasting the alternatives so you can pick what's best for your code. Begin with a hands-on introduction to object-relational mapping (ORM), then dive into mapping strategies for linking up objects and your database. You'll learn about the different approach to transactions for both Hibernate and Spring Data, and even how to deliver Java persistence with non-relational databases. Finally, you'll explore testing strategies for persistent applications to keep your code clean and bug free.

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Master essential best practices for deploying and managing applications on Amazon Web Services. The ideal guide for mid-level developers, DevOps or platform engineers, architects, and system administrators. Amazon Web Services in Action: An in-depth guide to AWS is a comprehensive, practical introduction to deploying and managing applications on the AWS cloud platform. This revised bestseller is packed with techniques for building highly available and scalable architectures and automating deployment with Infrastructure as Code. This book will show you how to: Leverage globally distributed data centres to launch virtual machines with EC2 Store and archive large volumes of data with EBS, S3, and EFS Persist and query data with highly available and scalable database systems with RDS and DynamoDB Enhance performance with caching data in-memory with ElastiCache and MemoryDB Use Infrastructure as Code to automate your cloud infrastructure Secure workloads running in the cloud with VPC and IAM Build fault-tolerant web applications with ALB and SQS Automate common sysadmin tasks with Lambda, CLI, and SDK Build cloud-native applications based on containers with AppRunner, ECS, Fargate About the technology Thousands of developers have chosen Amazon Web Services in Action: An in-depth guide to AWS to help them succeed with the AWS cloud. Readers love this all-practical handbook for its complete introduction to computing, storage, and networking, along with best practices for all core AWS services. Amazon Web Services, the leading cloud computing platform, offers customers APIs for on-demand access to computing services. Rich in examples and best practices of how to use AWS, this Manning bestseller is now released in its third, revised, and improved edition.

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Secure your Azure applications the right way with the expert DevSecOps techniques you'll learn in this essential handbook. For software and security engineers building and securing Azure applications. In Azure Security you'll learn vital security skills, including how to: Configure Conditional Access policies to implement secure access Implement Azure Web Application Firewall (WAF) on Application Gateway and Azure Front Door Deploy Azure Firewall Premium to monitor network activities for malicious activity Enable Microsoft Defender for Cloud to continuously assess your workloads for misconfiguration Use Microsoft Sentinel to create analytics rules to detect threats and suspicious activity Set up Azure Policy to ensure that resource states and deployment is compliant with your business rules About the technology Attacks against cloud-based applications are increasingly common and sophisticated. It's vital for any developer or resource owner to understand how to properly configure their Azure cloud environments and establish reliable security best practices. The Azure platform comes with dozens of built-in security tools to help keep your systems safe. This book will teach you exactly how to set them up for maximum effectiveness.

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Learn the hands-on skills you need to ace the Kubernetes exam and boost your career by becoming a Certified Kubernetes Administrator (CKA). For readers who know the basics of containers and Linux admin. No Kubernetes experience is required. Acing the Certified Kubernetes Administrator Exam will provide you with content and practical exercises according to the unique CKA test environment. This practical book takes you hands-on with all the exam objectives, including deploying containerised applications to Kubernetes, accessing an application from an ingress resource, backup and restoring. You will learn how to: Administer an application running on Kubernetes Troubleshoot errors inside a Kubernetes cluster Authenticate users and machines to the Kubernetes API Create persistent storage in Kubernetes Add additional functionality to an existing Kubernetes cluster Plus! Essential exam tips and exercises help you work out your mental muscle memory. Acing the Certified Kubernetes Administrator Exam is your fast track to becoming a Certified Kubernetes Administrator! Your expert exam tutor is Chad Crowell, whose courses have helped thousands of developers to understand Kubernetes and earn the coveted CKA certification. About the technology The Certified Kubernetes Administrator (CKA) exam proves your skills as a Kubernetes administrator and is a serious test of your competency. There are no multiple-choice questions or essays: the whole test is conducted from the command line, with you performing solutions directly in the terminal. Administered by the Linux Foundation, the certification is recognised by employers worldwide as a proof of your ability to configure and manage production-grade Kubernetes clusters.

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Build your first robots with Python and some cheap, basic components. This entertaining book guides you step by step! In Build Your Own Robot you''ll learn how to: Use cameras to capture photos and let your robot see Track faces using computer vision and OpenCV Control DC motors to drive your robot around Create a web-based app to control your robot over a network Write code for joysticks Read QR codes with your robot to find and identify objects About the technology There''s nothing quite like watching your code come alive in the real world. Robotics is a fun, fascinating discipline that lets you do just that. In this guide, you''ll build some fun robotic toys that will teach you serious robotics engineering skills like computer vision, networking, and computation.

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Dodge the common mistakes that even senior developers make, take full advantage of static analysis tools, and deliver robust and error-free Java code.Whenever you make a mistake writing Java, it''s almost guaranteed that someone else has made it before! In 100 Java Mistakes and How To Avoid Them you''ll learn about the common and the not-so-common antipatterns, errors, and tricky bits that trip up almost every Java developer.Inside 100 Java Mistakes and How To Avoid Them you will learn how to: Write better Java programs Recognize common mistakes during programming Create fewer bugs and save time for debugging and testing Get help from static analyzers during programming Configure static analysis tools to reduce the number of false reports Extend static analysis tools with custom plugins Each Java mistake in this handy guide comes with an illustrative c

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Create bulletproof, high-performance web apps and servers with Rust. In Rust Web Development you will learn: Handling the borrow checker in an asynchronous environment Creating web APIs and using JSON in Rust Graceful error handling Testing, tracing, logging, and debugging Deploying Rust applications Efficient database access Rust Web Development is a hands-on guide to building server-based web applications with Rust. If you've built web servers using Java, C#, or PHP, you'll instantly fall in love with the performance and development experience Rust delivers. This book shows you how to work efficiently using pure Rust, along with important Rust libraries such as tokio for async runtimes, warp for web servers and APIs, and reqwest to run external HTTP requests. about the technology Web development languages and libraries can be resource hungry, with poor safety for maintaining vital web services. Rust services perform better and guarantee better safety. Plus, Rust's awesome compiler gives you an amazing developer experience. You'll get the speed of low-level programming languages like C along with the ease-of-use you'd expect from high-level languages Python or Ruby, with a super strong compiler that automatically prevents common mistakes such as null pointers. about the book In Rust Web Development, you'll learn to build server-side web applications using the Rust language and its key libraries. If you know the basics of Rust, you'll quickly pick up some pro tips for setting up your projects and organizing your code. This book gets you hands-on fast, with numerous small and large examples. You'll get up to speed with how Rust streamlines backend development, implements authentication flows, and even makes it easier for your APIs to interact. As you go, you'll build a complete Q&A web service and iterate on your code chapter-by-chapter, just like a real development project. RETAIL SELLING POINTS • Handling the borrow checker in an asynchronous environment • Creating web APIs and using JSON in Rust • Graceful error handling • Testing, tracing, logging, and debugging • Deploying Rust applications • Efficient database access AUDIENCE For experienced web developers familiar with Java, Node, or Go, and the absolute basics of Rust

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"Do you want to learn how to creat your own virtual agent? If so, have I got the book for you!" - Thomas Joseph Heiman Design, develop, and deploy human-like AI solutions that chat with your customers, solve their problems, and streamline your support services. Creating Virtual Assistants: Chatbots that work teaches you to create the kind of AI-enabled chatbots that are revolutionizing the customer service industry. You'll learn to build effective conversational AI that can automate common inquiries and easily address your customers' most common problems. In Creating Virtual Assistants, you will learn how to: Pick the right virtual assistant type and channel for your needsWrite dialog with intentional tone and specificityTrain a virtual assistant classifier from the ground upCreate question-and-direct-response assistantsDesign and optimize a process flow for web and voiceTest your assistant's accuracy and plan out improvements This engaging and entertaining book delivers the essential technical and creative skills for designing successful virtual assistants, from coding process flows and training machine learning, to improving your written dialog. about the technologyVirtual assistants multiply the effectiveness of customer-facing communication. Great chatbots automate common tasks like gathering information, responding to questions, and improving product selections so human staff can work on more challenging problems. These powerful tools range from event classifiers that can act on an email message to conversational assistants that actually talk to your users! about the bookCreating Virtual Assistants is a hands-on guide to building custom virtual assistants for a wide variety of use cases. You'll dive right into developing an assistant capable of identifying top user requests and making a suitable response for each request type. Once you've got the basics, you'll master a multi-step process flow that can be easily adapted for both text and voice assistants. You'll learn how to hone your assistant by writing better dialog, training and improving its underlying machine learning, and spotting issues like abandonment and underperformance. By the time you're done, you'll be ready to deploy anything from a simple chatbot to a complex call center tool. about the readerFor software developers. Examples in Watson Assistant and in Python. about the authorAndrew R. Freed is a Master Inventor and Senior Technical Staff Member at IBM. He's the co-host of the AI Zen podcast. Andrew has extensive experience deploying high-volume virtual assistants and has been working in AI solutions since 2012.

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Kickstart a career in cyber security by learning how to adapt your existing technical and non-technical skills with Cyber Defenders' CareerGuide. Cyber Defenders' Career Guide unlocks your pathway to becoming a great security practitioner. You'll learn how toreliably enter the security field and quickly grow into your new career, following clear, practical advice that's based on research and interviews with hundreds of hiring managers. Author Alyssa Miller has spent over adecade in cyber security leadership and talent development, and she shares her unique perspective in this revealing industry guide. By some estimates, there are over 4 million unfilled jobs in cybersecurity. This important field is growing fast, with a huge demand for skilled recruits. But where do you start? How can you know you're ready? This book isyour invaluable guide to starting and navigating a rewarding security career.

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Privacy-Preserving Machine Learning is a practical guide to keeping ML data anonymous and secure. You'll learn the core principles behind different privacy preservation technologies, and how to put theory into practice for your own machine learning. Complex privacy-enhancing technologies are demystified through real world use cases forfacial recognition, cloud data storage, and more. Alongside skills for technical implementation, you'll learn about current and future machine learning privacy challenges and how to adapt technologies to your specific needs. By the time you're done, you'll be able to create machine learning systems that preserve user privacy without sacrificing data quality and model performance. Large-scale scandals such as the Facebook Cambridge Analytic a data breach have made many users wary of sharing sensitive and personal information. Demand has surged among machine learning engineers for privacy-preserving techniques that can keep users private details secure without adversely affecting the performance of models.

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Building and training deep learning models from scratch is costly, time-consuming, and requires massive amounts of data. To address this concern, cutting-edge transfer learning techniques enable you to start with pretrained models you can tweak to meet your exact needs. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre takes you hands-on with customizing these open source resources for your own NLP architectures. You’ll learn how to use transfer learning to deliver state-of-the-art results even when working with limited label data, all while saving on training time and computational costs. about the technologyTransfer learning enables machine learning models to be initialized with existing prior knowledge. Initially pioneered in computer vision, transfer learning techniques have been revolutionising Natural Language Processing with big reductions in the training time and computation power needed for a model to start delivering results. Emerging pretrained language models such as ELMo and BERT have opened up new possibilities for NLP developers working in machine translation, semantic analysis, business analytics, and natural language generation. about the book Transfer Learning for Natural Language Processing is a practical primer to transfer learning techniques capable of delivering huge improvements to your NLP models. Written by DARPA researcher Paul Azunre, this practical book gets you up to speed with the relevant ML concepts before diving into the cutting-edge advances that are defining the future of NLP. You’ll learn how to adapt existing state-of-the art models into real-world applications, including building a spam email classifier, a movie review sentiment analyzer, an automated fact checker, a question-answering system and a translation system for low-resource languages. what's inside Fine tuning pretrained models with new domain data Picking the right model to reduce resource usage Transfer learning for neural network architectures Foundations for exploring NLP academic literature about the readerFor machine learning engineers and data scientists with some experience in NLP. about the author Paul Azunre holds a PhD in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs. He founded Algorine Inc., a Research Lab dedicated to advancing AI/ML and identifying scenarios where they can have a significant social impact. Paul also co-founded Ghana NLP, an open source initiative focused using NLP and Transfer Learning with Ghanaian and other low-resource languages. He frequently contributes to major peer-reviewed international research journals and serves as a program committee member at top conferences in the field.

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Most businesses are far more interested in accurate forecasting and fraud detection using their existing structured datasets than identifying cats in YouTube videos. Powerful deep learning techniques can efficiently extract insight from the kind of structured data collected by most businesses and organisations. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. • The benefits and drawbacks of deep learning • Organizing data for your deep learning model • The deep learning stack • Measuring performance of your models For readers with an intermediate knowledge of Python, Jupyter notebooks, and machine learning.

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Azure Data Engineering teaches you how to design a reliable, performant, and cost-effective data infrastructure in Azure by progressively building a complete working analytics system. Readers should be comfortable with RDBMS systems like SQL Server and scripting using a language like PowerShell, Bash, or Python. Book examples use PowerShell and C#. The Microsoft Azure cloud is an ideal platform for data-intensive applications. Designed for productivity, Azure provides pre-built services that make collection, storage, and analysis much easier to implement and manage. The Microsoft Azure cloud platform can host virtually any sort of computing task, from simple web applications to full-scale enterprise systems. With many pre-built services for everything from data storage to advanced machine learning, Azure offers all the building blocks for scalable big data analysis systems including ingestion, processing, querying, and migration. • Azure cloud services architecture • Building a data warehouse in Azure • How to choose the right Azure technology for your task • Calculating fixed and variable costs • Hot and cold path analytics Richard Nuckolls is a senior developer building a big data analytics and reporting system in Azure. During his nearly 20 years of experience, he’s done server and database administration, desktop and web development, and more recently has led teams in building a production content management system in Azure.

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Description Vue.js is one of the fastest growing and most popular open-source JavaScript frameworks around. Vue's meteoric success is found in its simplicity and short learning curve, but few resources are available to teach you how to test a Vue application effectively and efficiently. Testing Vue.js Applications is a comprehensive guide to testing Vue components, methods, events, and output. Author Edd Yerburgh, creator of the Vue testing utility avoriaz, teaches readers how to set up effective testing practices. Key features · Creating and testing Vue mixins · Building and testing component output, method, and events · Running unit tests, snapshot tests, and end to end tests in Jest Audience Written for developers with an intermediate knowledge of JavaScript, HTML, and CSS and a basic understanding of Vue.js. Some experience with ES6 is helpful, but not required. About the technology Vue is a powerful web framework that changes the way you build web UI. To test applications built with Vue, you need to master a new set of tools and techniques designed to work with Vue's unique reactive design and the flexible collection of components that make up the Vue stack. Edd Yerburgh is an experienced JavaScript developer and Vue core contributor. He is the main author of the official Vue test library and a prominent figure in the Vue testing community.

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Description Aurelia is a web framework that makes it much easier to create single page web applications. Aurelia was written with ES6, so modern JavaScript design principles are baked in from the ground level. Aurelia in Action teaches readers how to build fantastic single page applications with the Aurelia framework. By the end of the book, readers will be able to tune, secure, and deploy their finished SPAs, giving them everything they need to create modern web apps for a modern world. Key features · Step-by-step instructions · Hands-on examples · Clear introduction Audience Written for developers comfortable with JavaScript and MVC-style web development. Some experience with ES6 is helpful, but not required. About the technology Adopting a Rails-like convention-over-configuration mindset, Aurelia makes it a snap to start even complex projects, because the most common design principles and best practices are implemented in new projects by default. Author biography Sean Hunter is a software developer in Melbourne, Australia with 9 years of web development experience.

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Description Vue.js is a front-end framework that builds on many of the reactive UI ideas introduced in React.js. Vue.js in Action teaches readers to build fast, flowing web UI with the Vue.js framework. As they move through the book, readers put their skills to practice by building a complete web store application with product listings, a checkout process, and an administrative interface! Key features · Add View and ViewModel interactivity · Work with components · Extend Vue.js with custom plugins and directives · Learn data modeling and consuming APIs Audience Written for web developers with beginning to intermediate in JavaScript, HTML, and CSS. About the technologyAs a second-generation reactive UI framework, Vue was designed from the ground up with developer usability in mind. It's far more intuitive than React, featuring a clean event lifecycle, easy two-way data binding, and a common-sense project structure.

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F# leads to quicker development time and a lower total cost of ownership. Its powerful feature set allows developers to more succinctly express their intent, and encourages best practices - leading to higher quality deliverables in less time. Programming with F#: A guide for .NET developers shows you how to upgrade your .NET development skills by adding a touch of functional programming in F#. In just 43 bite-size chunks, you’ll learn to use F# to tackle the most common .NET programming tasks. You’ll start with the basics of F# and functional programming, building on your existing skills in the .NET framework. Examples use the familiar Visual Studio environment, so you’ll be instantly comfortable. Packed with enlightening examples, real-world use cases, and plenty of easyto-digest code, this easy-to-follow tutorial will make you wonder why you didn’t pick up F# years ago! KEY FEATURES • Hands-on chapters • Practical examples • Bite-size lessons • Try This exercises For intermediate C# and Visual Basic .NET developers who have heard about F# and functional programming and want to understand the benefits and use it as a part of their existing toolbox without having to throw away existing code. ABOUT THE TECHNOLOGY F# is a mature, open-source functional-first language that's rapidly growing in popularity both inside and outside the .NET ecosystem. AUTHOR BIO Isaac Abraham is an F# MVP and a .NET developer since .NET 1.0 with an interest in cloud computing and distributed data problems. He lives in both the UK and Germany, and is the director of Compositional IT.

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　 DESCRIPTION R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data. R in Action, Second Edition is language tutorial focused on practical problems. Written by a research methodologist, it takes a direct and modular approach to quickly give readers the information they need to produce useful results. Focusing on realistic data analyses and a comprehensive integration of graphics, it follows the steps that real data analysts use to acquire their data, get it into shape, analyze it, and produce meaningful results that they can provide to clients. RETAIL SELLING POINTS Step-by-step guide to practical data analysis Gives quick access to the R language Written by seasoned researcher Uses over 130 graphics AUDIENCE This book is for social scientists, medical and pharmaceutical researchers, professors and students in quantitative fields, data analysts, data mining specialists, and statistical programmers who have a sense of what they want to do, but not how to do it in R. ABOUT THE TECHNOLOGY R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and

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Deep learning from the ground up using R and the powerful Keras library! In Deep Learning with R, Second Edition you will learn: Deep learning from first principles Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation Deep Learning with R, Second Edition shows you how to put deep learning into action. It's based on the revised new edition of François Chollet's bestselling Deep Learning with Python. All code and examples have been expertly translated to the R language by Tomasz Kalinowski, who maintains the Keras and Tensorflow R packages at RStudio. Novices and experienced ML practitioners will love the expert insights, practical techniques, and important theory for building neural networks. about the technology Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R. what's inside Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation about the reader For readers with intermediate R skills. No previous experience with Keras, TensorFlow, or deep learning is required.

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Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. In Time Series Forecasting in Python you will learn how to: Recognize a time series forecasting problem and build a performant predictive model Create univariate forecasting models that account for seasonal effects and external variables Build multivariate forecasting models to predict many time series at once Leverage large datasets by using deep learning for forecasting time series Automate the forecasting process DESCRIPTION Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You'll explore interesting real-world datasets like Google's daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.Time Series Forecasting in Python teaches you to apply time series forecasting and get immediate, meaningful predictions. You'll learn both traditional statistical and new deep learning models for time series forecasting, all fully illustrated with Python source code. Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You'll explore interesting real-world datasets like Google's daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow. about the technology Time series forecasting reveals hidden trends and makes predictions about the future from your data. This powerful technique has proven incredibly valuable across multiple fields—from tracking business metrics, to healthcare and the sciences. Modern Python libraries and powerful deep learning tools have opened up new methods and utilities for making practical time series forecasts. about the book Time Series Forecasting in Python teaches you to apply time series forecasting and get immediate, meaningful predictions. You'll learn both traditional statistical and new deep learning models for time series forecasting, all fully illustrated with Python source code. Test your skills with hands-on projects for forecasting air travel, volume of drug prescriptions, and the earnings of Johnson & Johnson. By the time you're done, you'll be ready to build accurate and insightful forecasting models with tools from the Python ecosystem.

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A practical collection of the most important Python techniques. For beginning to intermediate Python programmers. Python How-To by Yong Cui, walks you through the most important coding techniques in Python. Whether you are doing data science, building web applications, or writing admin scripts, you will find answers to your “how-to” questions in this book. Author Yong Cui's clear and practical writing is perfect for beginners and veterans alike, with insightful code snippets, interesting graphics, and challenging exercises. Python How-To includes over 60 detailed answers to questions like: How do I join and split strings? How do I access dictionary keys, values, and items? How do I set and use the return value in function calls? How do I process JSON data? How do I create lazy attributes to improve performance? How do I change variables in a different namespace? ... and much more Along the way, you will also learn how to take advantage of Python's versatile tools and libraries. About the technology No matter where you are on your Python journey, you will run into situations where you ask yourself: “How do I do that?” This book provides concrete answers to the most common questions in areas such as manipulating text, working with collections, managing objects and functions, file management, etc.

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"This book will teach you everything you need to build and deploy kubernetes native microservices in a super productive fashion: a must!" - Alain Lompo Build fast, efficient Kubernetes-based Java applications using the Quarkus framework, MicroProfile, and Java standards. Most popular Java frameworks, like Spring, were designed long before the advent of Kubernetes and cloud-native systems. A new generation of tools, including Quarkus and MicroProfile have been cloud-native and Kubernetes-aware from the beginning. Kubernetes Native Microservices: With Quarkus and MicroProfile teaches you how to create efficient enterprise Java applications that are easy to deploy, maintain, and expand. In Kubernetes Native Microservices: With Quarkus and MicroProfile you'll learn how to: Deploy enterprise Java applications on KubernetesDevelop applications using the Quarkus runtime frameworkCompile natively using GraalVM for blazing speedCreate efficient microservices applicationsTake advantage of MicroProfile specifications about the technologyModern enterprise Java applications have embraced microservices, containers, Kubernetes, and a cloud-native approach. The Quarkus framework, developed at Red Hat, is designed for this deployment model, making cloud-native application development in Java much easier than it is on Spring or other older platforms. Quarkus applications compiled natively to GraalVM can deliver extremely fast runtimes, potentially improving performance by 100x or more. about the bookKubernetes Native Microservices: With Quarkus and MicroProfile introduces a modern approach to enterprise Java development using new tools designed for cloud-native applications. This book begins by exploring the impact Kubernetes and cloud systems have on your application design. Then, it quickly guides you through setting up an application using MicroProfile APIs, Kubernetes, and Quarkus. Using carefully selected examples and crystal-clear explanations, it guides you step by step from design to deployment. Written by veteran Java developers John Clingan and Ken Finnigan, this book oozes with experience and insight. You'll look past the ideal-but-untested advice you find in many books on new technologies and see how Kubernetes-native development with Quarkus and MicroProfile work in the real world. about the readerWritten for intermediate Java developers comfortable with Java EE, Jakarta EE, or Spring. Assumes some prior exposure to Docker and Kubernetes. No experience with Quarkus or MicroProfile required. about the authorJohn Clingan is a senior principal product manager at Red Hat. At Red Hat John works on next generation platforms including Quarkus. He is a co-founder of Eclipse MicroProfile, MicroProfile committer, and MicroProfile co-lead. Ken Finnigan is a senior principal software engineer and Eclipse MicroProfile technical architect at Red Hat. He's the co-founder of Eclipse MicroProfile and a MicroProfile committer.

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Spring is a massive ecosystem and a must-learn tool for Java developers. Spring Start Here introduces you to Java development with Spring by concentrating on the core concepts you'll use in every application you build. You'll learn how to refactor an existing application to Spring, how to use Spring tools to make SQL database requests and REST calls, and how to secure your projects with Spring Security. Spring Start Here teaches you how to build professional-quality applications using Spring and Spring Boot. You'll start with the core components of the framework and then learn how features like Spring Boot simplify the tedious repetitive tasks you face in every project. When you're done, you'll be able to create Spring apps, secure them with authentication and authorization, and move on to the next exciting steps of your Spring journey. Spring Framework is packed with features to make your applications fast, maintainable, robust and secure. This extensive ecosystem of tools for cloud computing, microservices, and more have made it the de facto choice for building enterprise Java applications.

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An effective DBA is an efficient DBA. And if you work with SQL Server, dbatools is a lifesaver. With over 500 commands, this free and open source PowerShell module has the horsepower to automate just about every task you can imagine—and then some! Learn dbatools in a Month of Lunches teaches you techniques that will make you more effective—and efficient—than you ever thought possible. Learn dbatools in a Month of Lunches is a practical hands-on guide to automating SQL Server with PowerShell and the awesome dbatools module. You'll master techniques you can immediately put into practice, from daily duties like backups and restores right through to performing security audits. Stabilize and standardize your SQL server environment, and simplify your tasks by building automation, alerting, and reporting with this powerful tool. Each lesson delivers another skill that you can use to speed through your core tasks as a SQL Server DBA! About the TechnologyWant to automate tasks for thousands of SQL servers at once? Want to migrate an entire SQL server using just the command line? dbatools can do all that—and more. A free and open source PowerShell module, dbatools offers over 500 commands for automating SQL Server from the command line. Boasting advanced options unavailable in official tools, dbatools makes it easy to automate tasks including mass exports for simplified disaster recovery, tempdb configuration, and improving an instance's security posture.

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Built specifically for statistical computing and graphics, the R language, along with its amazing collection of libraries and tools, is one of the most powerful tools you can use to tackle data analysis for business, research, and other data-intensive domains. This revised and expanded third edition of R in Action covers the new tidy verse approach to data analysis and R's state-of-the-art graphing capabilities with the ggplot2 package. R in Action, Third Edition teaches you to use the R language, including the popular tidy verse packages, through hands-on examples relevant to scientific, technical, and business developers. Focusing on practical solutions to real-world data challenges, R expert RobKabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualisations. The R language is the most powerful platform you can choose for modern data analysis. Free and open source, R's community has created thousands of modules to tackle challenges from data-crunching to presentation. R's graphical capabilities are also state-of-the-art, with a comprehensive and powerful feature set available for data visualization. R runs on all major operating systems and is used by businesses, researchers, and organizations worldwide.

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Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. • Foundational reinforcement learning concepts and methods • The most popular deep reinforcement learning agents solving high-dimensional environments • Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

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Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you’ll need to implement it into your own projects. Key features • Structuring problems as Markov Decision Processes • Popular algorithms such Deep Q-Networks, Policy Gradient method and Evolutionary Algorithms and the intuitions that drive them • Applying reinforcement learning algorithms to real-world problems Audience You’ll need intermediate Python skills and a basic understanding of deep learning. About the technology Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior from their own raw sensory input. The system perceives the environment, interprets the results of its past decisions, and uses this information to optimize its behavior for maximum long-term return. Deep reinforcement learning famously contributed to the success of AlphaGo but that’s not all it can do! Alexander Zai is a Machine Learning Engineer at Amazon AI working on MXNet that powers a suite of AWS machine learning products. Brandon Brown is a Machine Learning and Data Analysis blogger at outlace.com committed to providing clear teaching on difficult topics for newcomers.

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Description Fully updated to include the latest revisions and updates to AWS; this new edition also offers three new chapters covering the latest additions to the AWS platform: serverless infrastructure automation with AWS Lambda, sharing data volumes between machines with EFS, and caching data in memory with ElastiCache! Amazon Web Services in Action, Second Edition is a comprehensive introduction to computing, storing, and networking in the AWS cloud. Readers will find clear, relevant coverage of all the essential AWS services they need to know, emphasizing best practices for security, high availability and scalability. Key features · Hands-on guide · Practical examples · Step-by-step instructions Audience Written for developers and DevOps engineers moving distributed applications to the AWS platform. About the technology AWS is known as a cloud computing platform. Cloud computing, or the cloud, is a metaphor for supply and consumption of IT resources. The IT resources in the cloud aren’t directly visible to the user; there are layers of abstraction in between.

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The idea behind Docker is simple. Create a tiny virtual environment called a container that holds just your application and its dependencies. The Docker engine uses the host operating system to keep track of your containers. Applications running inside containers share resources, making their footprints small. They are easy to install, manage, and remove. Docker in Action, Second Edition teaches you to create, deploy, and manage applications hosted in Docker containers running on Linux. Fully updated, with four new chapters and revised best practices and examples, this second edition begins with a clear explanation of the Docker model. Then, you go hands-on with packaging applications, testing, installing, running programs securely, and deploying them across a cluster of hosts. With examples showing how Docker benefits the whole dev lifecycle, you'll discover techniques for everything from dev-and-test machines to full-scale cloud deployments.

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Description Why use several languages for a web application when you only need one? Node.js is a server-side platform and runtime that readers can use to build full stack web applications entirely in JavaScript! Get Programming with Node.js teaches readers to write server-side code in JavaScript using Node.js. In 34 fast-paced, fun, and practical lessons, readers discover how to extend their existing JavaScript skills to write back-end code for their web applications. Key features · Fast-paced · Practical lessons · Hands-on guide Audience Written for developers who know HTML, CSS, and JavaScript. No prior experience with Node.js is required. About the technology Node supports scalable, high-performance applications with easy asynchronous communication, an event-driven mindset, and a vast ecosystem of tools and modules. Node can handle the real-time response rates that games, chat sites, and statistical services need, and you get to program everything in JavaScript. Author biography Jonathan Wexler has an extensive background in computer theory and web development. Having curated a Node.js curriculum as the academic director and lead developer for The New York Code and Design Academy, Jonathan has instructed multiple intensive programs in full stack development and currently works as a senior developer for Bloomberg LP.

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Description All aspects of software development and deployment become painfully slow. The solution is to adopt the microservice architecture. This architecture accelerates software development and enables continuous delivery and deployment of complex software applications. Microservice Patterns teaches enterprise developers and architects how to build applications with the microservice architecture. This book also teaches readers how to refactor a monolithic application to a microservice architecture. Key features · In-depth guide · Practical examples · Step-by-step instructions Audience Readers should be familiar with the basics of enterprise application architecture, design, and implementation. About the technology Microservice architecture accelerates software development and enables continuous delivery and deployment of complex software applications. Author biography Chris Richardson is a developer and architect. He is a Java Champion, a JavaOne rock star and the author of POJOs in Action, which describes how to build enterprise Java applications with frameworks such as Spring and Hibernate. Chris was also the founder of the original CloudFoundry.com, an early Java PaaS for Amazon EC2. Today, he is a recognized thought leader in microservices. Chris is the creator of http://microservices.io , a website describing how to develop and deploy microservices. He provides microservices consulting and training and is working on his third startup http://eventuate.io , an application platform for developing microservices.

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Kotlin is a new programming language targeting the Java platform. Itoffers on expressiveness and safety without compromising simplicity,seamless interoperability with existing Java code, and great toolingsupport. Because Kotlin generates regular Java bytecode and workstogether with existing Java libraries and frameworks, it can be usedalmost everywhere where Java is used today - for server-sidedevelopment, Android apps, and much more. Kotlin in Action takes experienced Java developers from the languagebasics all the way through building applications to run on the JVM andAndroid devices. Written by core developers of Kotlin, this examplerichbook begins by teaching the basic syntax of the Kotlin language.Then readers learn how to use features that let them build reusableabstractions, higher-level functions, libraries, and even entire domainspecific languages. Finally, the book focuses on details of applyingKotlin in real-world projects, such as build system integration, Androidsupport and concurrent programming. KEY FEATURES • Hands on examples• Tutorial for a new programming language• Teaches how to build Android applications• Written by core developers of Kotlin AUDIENCEThis book is for experienced Java developers. ABOUT THE TECHNOLOGYKotlin is a new programming language targeting the Java platform. It offersexpressiveness and safety without compromising simplicity, seamlessinteroperability with existing Java code, and great tooling support.

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The Internet of Things (IoT) is a hot topic! Analysts call it a disruptive technology. Competing standards and technologies pop up daily, and there are no tangible signs of a single protocol that will let all devices, services, and applications communicate seamlessly. Fortunately, there's a great universal IoT application platform available now: the World Wide Web. Web standards and tools provide the ideal substrate for connected devices and applications to exchange data. This vision is called the Web of Things. Building the Web of Things is a hands-on guide for designing and implementing scalable, flexible, and open IoT solutions using Web technologies. This book provides the right balance of theory, code samples, and practical examples, and shows how to connect all sorts of devices to the Web and expose their services and data over REST APIs. After building a simple proof of concept app, readers will learn a systematic methodology and system architecture for connecting things to the Web, finding other things, sharing data, and combining these components to rapidly build distributed applications and physical mashups. With each chapter, readers gain the knowledge and skills needed to take full advantage of a new generation of real-time, web-connected devices and services, giving them the ability to build scalable applications that merge the physical and digital worlds. KEY FEATURES Gets readers started with the Web of Things in minutes Offers a complete toolbox of Web and Internet technologies Hands-on guide for using the web to connect apps to the real world ABOUT THE TECHNOLOGY The Web of Things is about using the latest Web technologies as the underlying application-level protocol for the Internet of Things (IoT). While the Internet of Things mainly focuses on the networking side of how to connect things, the Web of Things focuses on the application layer, i.e., how things can expose and share their data and services so that they can easily be consumed by Web applications.

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Master the geometry behind CAD, game engines, GIS, and more! Geometry for Programmers is a hands-on book teaching you the maths behind the tools and libraries to create simulations, 3D prints, and other models in the physical world. Ideal for developers writing code using CAD libraries, game engines, or rendering tools, the textbook guides you through the math behind graphics and modelling tools using relevant examples and clear explanations that don't require advanced mathematical knowledge. You will learn how mastering manual geometry can help you avoid code layering and repetition and even how to drive down cloud hosting costs by creating more efficient application runtimes. Key features include: Speak the language of applied geometry Compose geometric transformations economically Craft custom splines for efficient curves and surface generation Pick and implement the right geometric transformations Confidently use important algorithms that operate on triangle meshes, distance functions, and voxels Filled with charts, illustrations, and complex equations rendered as simple Python code, this book unlocks geometry in a way you can apply it to your daily work. About the technology Geometry is the core of game engines, computer-aided design, image-processing libraries, GIS, and much more. Understanding the mathematical underpinnings of tools and libraries empowers you to develop more efficient programming strategies. This unique guide gives you control over the geometry you need to deliver faster, cleaner results— and even build your own geometry tools!

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The go-to guide in machine learning projects from design to production. No ML skills required! In Managing Machine Learning Projects, you will learn essential machine learning project management techniques, including: Understanding an ML project's requirements Setting up the infrastructure for the project and resourcing a team Working with clients and other stakeholders Dealing with data resources and bringing them into the project for use Handling the lifecycle of models in the project Managing the application of ML algorithms Evaluating the performance of algorithms and models Making decisions about which models to adopt for delivery Taking models through development and testing Integrating models with production systems to create effective applications Steps and behaviours for managing the ethical implications of ML technology About the technology Companies of all shapes, sizes, and industries are investing in machine learning (ML). Unfortunately, around 85% of all ML projects fail. Managing machine learning projects requires adopting a different approach than you would take with standard software projects. You need to account for large and diverse data resources, evaluate and track multiple separate models, and handle the unforeseeable risk of poor performance. Never fear — this book lays out the unique practices you will need to ensure your projects succeed!

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Enter the Web Design Playground and start experimenting with all aspects of creating a web page—from design, to development, to publishing—in an easy-to-use free online workspace. Suitable for anyone interested in creating web pages. In Web Design Playground, Second Edition you'll learn essential tools of the web design trade, such as: Structuring a web page with HTML Styling a web page with CSS Modern page layout techniques Using colors in web design Making text look awesome with typography About the technology HTML, CSS, and the principles of good web design are all you need to build something beautiful! You'll find them all inside this one-of-a-kind guide. Written by web designer and master teacher Paul McFedries, this unique book shapes and sharpens your skills in the always-relevant technologies of the web.

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DESCRIPTION AngularJS has rapidly become the most popular web development framework for browser-based applications, but it's not a great solution for mobile apps. Ionic, an open source framework, blends the best features of AngularJS with Cordova (previously known as Phonegap) to package web applications into a native-quality mobile app. In other words, it allows users to build mobile apps using the web technologies they already know and love. Ionic does all the heavy lifting using CSS and JavaScript so users can get clean, native looking cross-platform apps without the hassle of building separate native apps for iOS and Android. Ionic in Action teaches web developers how to build cross-platform mobile apps for phones and tablets. It helps them extend their web development skills to build apps that are indistinguishable from native iOS or Android projects. With carefully explained examples the book shows how to build several mobile apps that demonstrate mobile-specific features such as GPS, camera, notifications, UI controls, and integrating with external data sources. Lastly, the book covers ways to test apps to improve stability and catch errors during development. KEY SELLING POINTS Covers the entire mobile development process Best practices for building mobile apps Sample apps demonstrate wide set of available features AUDIENCE The reader should be experienced in web development with HTML, CSS, and JavaScript. Some familiarity with AngularJS is helpful but not required. ABOUT THE TECHNOLOGY AngularJS is the most popular web development framework for browser-based applications. Ionic, an open source framework, blends the best features of AngularJS with Cordova (previously known as Phonegap) to package web applications into a native-quality mobile app. The book teaches how to build mobile apps for phones and tablets that work on both Apple or Google based operating systems, iOS and Android.

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Fully updated to ASP.NET 5.0, ASP.NET Core in Action, Second Edition is a hands-on primer to building cross-platform web applications with your C# and .NET skills. Even if you’ve never worked with ASP.NET you’ll start creating productive cross-platform web apps fast. And don’t worry about late-breaking changes to ASP.NET Core. With this Manning Early Access Program edition you’ll get updates right up until it ships to the printer, so you’re always working with the latest version of the technology. about the technologyASP.NET Core is a highly flexible, high performance cross platform web framework that’s entirely free and open source. ASP.NET Core developers enjoy choice without compromise, benefiting from both a mature, well-supported stack and the freedom to develop and deploy from and onto any cloud or on-prem platform. Now in version 5.0, the latest version of ASP.NET Core includes powerful new additions for building server-side apps and background services. about the book ASP.NET Core in Action, Second Edition opens up the world of cross-platform web development with ASP.NET Core. You’ll start with a crash course in .NET Core, immediately cutting the cord between ASP.NET and Windows. Then, you’ll begin to build amazing web applications step by step, systematically adding essential features like logins, configuration, dependency injection, and custom components. Along the way, you’ll mix in important process steps like testing, multiplatform deployment, and security. Fully updated to version 5.0, this new edition fully covers new features such as server-side apps with Razor Pages, and the new ASP.NET Core hosting paradigm. what's inside Covers ASP.NET Core 5.0 Dynamic page generation with the Razor templating engine Server-side apps with Razor Pages Authentication and authorization Unit tests and integration tests for ASP.NET Core apps Create a Web API for serving JSON to client-side applications Developing ASP.NET Core apps for non-Windows servers about the readerReaders need intermediate experience with C# or a similar language. about the author Andrew Lock is a Microsoft MVP who has been working with ASP.NET Core since before the first release. He has a PhD in digital image processing, and has been developing professionally using .NET for the last 10 years.

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When it comes to data analytics, it pays tothink big. PySpark blends the powerful Spark big data processing engine withthe Python programming language to provide a data analysis platform that can scaleup for nearly any task. Data Analysis with Python and PySpark is yourguide to delivering successful Python-driven data projects. Data Analysis with Python and PySpark is a carefully engineered tutorial that helps you use PySpark to deliver your data-driven applications at any scale. This clear and hands-on guide shows you how to enlarge your processing capabilities across multiple machines with data from any source, ranging from Had oop-based clusters to Excel worksheets. You'll learn how to break down big analysis tasks into manageable chunks and how to choose and use the best PySpark data abstraction for your unique needs. The Spark data processing engine is an amazing analytics factory: raw data comes in,and insight comes out. Thanks to its ability to handle massive amounts of data distributed across a cluster, Spark has been adopted as standard by organizations both big and small. PySpark, which wraps the core Spark engine with a Python-based API, puts Spark-based data pipelines in the hands of programmers and data scientists working with the Python programming language. PySpark simplifies Spark's steep learning curve, and provides a seamless bridge between Spark and an ecosystem of Python-based data science tools.

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Getting Started with Natural Language Processing is a hands-on guide filled with everything you need to get started with NLP in a friendly, understandable tutorial. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away. By following the numerous Python-based examples and real-world case studies, you’ll apply NLP to search applications, extracting meaning from text, sentiment analysis, user profiling, and more. When you’re done, you’ll have a solid grounding in NLP that will serve as a foundation for further learning. Key Features · Extracting information from raw text · Named entity recognition · Automating summarization of key facts · Topic labeling For beginners to NLP with basic Python skills. About the technology Natural Language Processing is a set of data science techniques that enable machines to make sense of human text and speech. Advances in machine learning and deep learning have made NLP more efficient and reliable than ever, leading to a huge number of new tools and resources. From improving search applications to sentiment analysis, the possible applications of NLP are vast and growing. Ekaterina Kochmar is an Affiliated Lecturer and a Senior Research Associate at the Natural Language and Information Processing group of the Department of Computer Science and Technology, University of Cambridge. She holds an MA degree in Computational Linguistics, an MPhil in Advanced Computer Science, and a PhD in Natural Language Processing.

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Using standards like OpenAPI, you can provide reliable, easy-to-use interfaces that allow other developers safe, controlled access to your software. Designing APIs withSwagger and OpenAPI is a hands-on primer to properly designing and describing your APIs using the most widely-adopted standard. Designing APIswith Swagger and OpenAPI introduces you to a design-first paradigm that will teach you the best practices for describing and designing RESTful APIs using OpenAPI and Swagger. You'll build upon progressively-enhanced examples as you learn to describe an API andthen extend it in the kind of scenarios you'd encounter in the real world. As you go, you'll use the popular Open Source tools to define APIs, generate documentation, and build other developer-friendly components like mocks, server stubs, and client SDKs. Modern web applications are made of multiple components, services, and servers connected through APIs, often using HTTP and REST as their primary interfaces. These architectures rely on APIs that allow access to the functionality of a component without requiring developers to understand the details of how it was implemented. The OpenAPI specification standardizes how you describe RESTful APIs. OpenAPI is vendor-neutral and has been adopted bybig tech companies such as Google, Microsoft, and Amazon.

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The mathematical paradigms that underlie deep learning typically start out as hard-to-read academic papers, often leaving engineers in the dark about how their models actually function. Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. Written by deep learning expert Krishnendu Chaudhury, you'll peer inside the “black box” to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications. about the technology It's important to understand how your deep learning models work, both so that you can maintain them efficiently and explain them to other stakeholders. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You'll be free from blind reliance on pre-packaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you'll be glad you can quickly identify and fix problems. about the book Math and Architectures of Deep Learning sets out the foundations of DL in a way that's both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You'll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. By the time you're done, you'll have a combined theoretical insight and practical skills to identify and implement DL architecture for almost any real-world challenge.

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