Using a web API to provide services to application developers is one of the more satisfying endeavors that software engineers undertake. But building a popular API with a thriving developer ecosystem is also one of the most challenging. With this practical guide, developers, architects, and tech leads will learn how to navigate complex decisions for designing, scaling, marketing, and evolving interoperable APIs.Authors Brenda Jin, Saurabh Sahni, and Amir Shevat explain API design theory and provide hands-on exercises for building your web API and managing its operation in production. Youll also learn how to build and maintain a following of app developers. This book includes expert advice, worksheets, checklists, and case studies from companies including Slack, Stripe, Facebook, Microsoft, Cloudinary, Oracle, and GitHub.Get an overview of request-response and event-driven API design paradigmsLearn best practices for designing an API that meets the needs of your usersUse a template to create an API design processScale your web API to support a growing number of API calls and use casesRegularly adapt the API to reflect changes to your product or businessProvide developer resources that include API documentation, samples, and tools
This book provides a highly practical look at ES6, without getting lost in the specification or its implementation details. Armed with practical examples, author Nicolas Bevacqua shows you new ways to deal with asynchronous flow control, declare objects or functions, and create proxies or unique sets, among many other features.
You have a mound of data front of you and a suite of computation tools at your disposal. Which parts of the data actually matter? Where is the insight hiding? If youre a data scientist trying to navigate the murky space between data and insight, this practical book shows you how to make sense of your data through high-level questions, well-defined data analysis tasks, and visualizations to clarify understanding and gain insights along the way.When incorporated into the process early and often, iterative visualization can help you refine the questions you ask of your data. Authors Danyel Fisher and Miriah Meyer provide detailed case studies that demonstrate how this process can evolve in the real world.Youll learn:The data counseling process for moving from general to more precise questions about your data, and arriving at a working visualizationThe role that visual representations play in data discoveryCommon visualization types by the tasks they fulfill and the data they useVisualization techniques that use multiple views and interaction to support analysis of large, complex data sets
What separates the traditional enterprise from the likes of Amazon, Netflix, and Etsy? Those companies have refined the art of cloud native development to maintain their competitive edge and stay well ahead of the competition. This practical guide shows Java/JVM developers how to build better software, faster, using Spring Boot, Spring Cloud, and Cloud Foundry.Many organizations have already waded into cloud computing, test-driven development, microservices, and continuous integration and delivery. Authors Josh Long and Kenny Bastani fully immerse you in the tools and methodologies that will help you transform your legacy application into one that is genuinely cloud native.In four sections, this book takes you through:The Basics: learn the motivations behind cloud native thinking; configure and test a Spring Boot application; and move your legacy application to the cloudWeb Services: build HTTP and RESTful services with Spring; route requests in your distributed system; and build edge services closer to the dataData Integration: manage your data with Spring Data, and integrate distributed services with Springs support for event-driven, messaging-centric architecturesProduction: make your system observable; use service brokers to connect stateful services; and understand the big ideas behind continuous delivery
Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learningespecially deep neural networksmake a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks.Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, youll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J.Dive into machine learning concepts in general, as well as deep learning in particularUnderstand how deep networks evolved from neural network fundamentalsExplore the major deep network architectures, including Convolutional and RecurrentLearn how to map specific deep networks to the right problemWalk through the fundamentals of tuning general neural networks and specific deep network architecturesUse vectorization techniques for different data types with DataVec, DL4Js workflow toolLearn how to use DL4J natively on Spark and Hadoop
The infrastructure-as-code revolution in IT is also affecting database administration. With this practical book, developers, system administrators, and junior to mid-level DBAs will learn how the modern practice of site reliability engineering applies to the craft of database architecture and operations. Authors Laine Campbell and Charity Majors provide a framework for professionals looking to join the ranks of todays database reliability engineers (DBRE).Youll begin by exploring core operational concepts that DBREs need to master. Then youll examine a wide range of database persistence options, including how to implement key technologies to provide resilient, scalable, and performant data storage and retrieval. With a firm foundation in database reliability engineering, youll be ready to dive into the architecture and operations of any modern database.This book covers:Service-level requirements and risk managementBuilding and evolving an architecture for operational visibilityInfrastructure engineering and infrastructure managementHow to facilitate the release management processData storage, indexing, and replicationIdentifying datastore characteristics and best use casesDatastore architectural components and data-driven architectures
Do you want to build mobile games, but lack game development experience? No problem. This practical guide shows you how to create beautiful, interactive content for iOS and Android devices with the Unity game engine.
A maker's home is their DIY palace. From simple personalization to tricking out a custom connected home, Make: Volume 59 is all about adding maker flair to your abode. In this issue you'll make a NeoPixel map to track the traffic for your morning commute, build a levitating planter straight from the future, and learn how to automatically water your garden.Plus 13 projects inside, including:Build a DIY thermal imaging cameraPrank your friends with a pint-sized, noise-making throwie3D print an articulated blooming flower night lightLearn to code with the BBC micro:bit and Make:CodeAnd more!
GraphQL, a data query language that provides an alternative to REST and ad-hoc webservice architectures, is the most revolutionary technology for data fetching since Ajax. Just as React has changed the way web developers approach UI, GraphQL will change the way web developers work with data over HTTP. This practical guide simplifies the process of getting started with this language.Alex Banks and Eve Porcello, software engineers/architects and instructors, start with an overview of graph theory to provide a solid understanding of the powerful graph data structure. You'll then learn about GraphQL types, as well as how to build a schema to describe your API. This book also includes an overview of Apollo and Relay, two popular frameworks that are used to connect GraphQL to your user interface.
The results are in for our 6th annual Desktop Digital Fabrication Shoot Out! Make: Volume 60 has more than 30 reviews that show off the latest and greatest FDM and resin 3D printers, CNC machines, laser cutters, and vinyl cutters, including new machines from Ultimaker, Prusa, Lulzbot, ShopBot, and Glowforge.
What will you learn from this book?Go makes it easy to build software thats simple, reliable, and efficient. Andthis book makes it easy for programmers like you to get started. Googledesigned Go for high-performance networking and multiprocessing, butlike Python and JavaScriptthe language is easy to read and use. With thispractical hands-on guide, youll learn how to write Go code using clearexamples that demonstrate the language in action. Best of all, youll understandthe conventions and techniques that employers want entry-level Godevelopers to know.Why does this book look so different?Based on the latest research in cognitive science and learning theory, HeadFirst Go uses a visually rich format to engage your mind rather than a textheavyapproach that puts you to sleep. Why waste your time struggling withnew concepts? This multisensory learning experience is designed for theway your brain really works.
In this fully updated second edition, you'll learn how to build custom plugins, themes, and services for just about any kind of web or mobile application.
If you have a working knowledge of JavaScript and ECMAScript 6 (ES6), this practical guide will help you tackle modular programming to produce code thats readable, maintainable, and scalable. Youll learn the fundamentals of modular architecture with JavaScript and the benefits of writing self-contained code at every system level, including the client and server.Nicols Bevacqua, author of Practical Modern JavaScript, demonstrates how to scale out JavaScript applications by breaking codebases into smaller modules. By following the design practices in this book, senior developers, technical leaders, and software architects will learn how to create modules that are simple and flexible while keeping internal complexity in check.Learn modular design essentials, including how your application will be consumed and what belongs on the interfaceDesign module internals to keep your code readable and its intent clearReduce complexity by refactoring code and containing and eliminating stateTake advantage of modern JavaScript features to write clear programs and reduce complexityApply Twelve-Factor App principles to frontend and backend JavaScript application development
This full-color, illustrated handbook uses comic book-style panels to explain the basics of using a breadboard; then it walks you through ten fun and educational projects. You'll learn-by-doing as you study the circuit diagrams and colorful drawings.
For many organizations, a big part of DevOps appeal is software automation using infrastructure-as-code techniques. This book presents developers, architects, and infra-ops engineers with a more practical option. Youll learn how a container-centric approach from OpenShift, Red Hats cloud-based PaaS, can help your team deliver quality software through a self-service view of IT infrastructure.Three OpenShift experts at Red Hat explain how to configure Docker application containers and the Kubernetes cluster manager with OpenShifts developer- and operational-centric tools. Discover how this infrastructure-agnostic container management platform can help companies navigate the murky area where infrastructure-as-code ends and application automation begins.Get an application-centric view of automationand understand why its importantLearn patterns and practical examples for managing continuous deployments such as rolling, A/B, blue-green, and canaryImplement continuous integration pipelines with OpenShifts Jenkins capabilityExplore mechanisms for separating and managing configuration from static runtime softwareLearn how to use and customize OpenShifts source-to-image capabilityDelve into management and operational considerations when working with OpenShift-based application workloadsInstall a self-contained local version of the OpenShift environment on your computer
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, "e;What are you trying to do and why?"e;Wrangling data consumes roughly 50-80% of an analysts 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 factorstime, granularity, scope, and structurethat you need to consider as you begin to work with data. Youll learn a shared language and a comprehensive understanding of data wrangling, with an emphasis on recent agile analytic processes used by many of todays data-driven organizations.Appreciate the importanceand the satisfactionof wrangling data the right way.Understand what kind of data is availableChoose which data to use and at what level of detailMeaningfully combine multiple sources of dataDecide how to distill the results to a size and shape that can drive downstream analysis
What will you learn from this book?Swift is best known as Apple's programming language of choice for developing apps on iOS, iPadOS, macOS, watchOS, and tvOS. But it's far more versatile than that. Open source Swift is also gaining ground as a language for systems programming and server-side code, and it runs on Linux and Windows. So where do you start? With Head First Swift, you'll explore from the ground up: from collecting and controlling data to reusing code, producing custom data types, and structuring programs and user interfaces with SwiftUI by building safe, protocol-driven code. With Swift under your belt, you'll be ready to build everything from mobile and web apps to games, frameworks, command-line tools, and beyond.What's so special about this book?If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. With this book, you'll learn Swift through a multisensory experience that engages your mind rather than a text-heavy approach that puts you to sleep.
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.
If you're grounded in the basics of Swift, Xcode, and the Cocoa framework, this book provides a structured explanation of all essential real-world iOS app components. Through deep exploration and copious code examples, you'll learn how to create views, manipulate view controllers, and add features from iOS frameworks
Tackling an app development project on multiple platforms is no simple task. When time is in short supply and customers need access from the tap of a home screen, React Native can provide a lean development team with the tools needed to deliver a multi-platform native experience without juggling multiple programming languages and shifting code bases. React Native is an emerging technology and best practices are only beginning to bubble up.Fortunately, a growing user communityfrom tech giants such as Facebook, Yahoo, and Airbnb to the independent developersis hard at work codifying patterns and best practices for how to use React Native. This cookbook is another milestone on that journey.Aimed at people with some JavaScript and web development experience, the first part of this cookbook covers some simple tips for getting started with React Native. Part 2 will cover some emerging patterns that are commonly found in most native applications.
Take full creative control of your web applications with Flask, the Python-based microframework. With the second edition of this hands-on book, you'll learn the framework from the ground up by developing, step-by-step, a real-world project created by author Miguel Grinberg.
Learn how to solve challenging machine learning problems with Tensorflow, Googles revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus, this practical book shows you how to buildand when to usedeep learning architectures. Youll learn how to design systems capable of detecting objects in images, understanding human speech, analyzing video, and predicting the properties of potential medicines.TensorFlow for Deep Learning teaches concepts through practical examples and builds understanding of deep learning foundations from the ground up. Its ideal for practicing developers comfortable with designing software systems, but not necessarily with creating learning systems. This book is also useful for scientists and other professionals who are comfortable with scripting, but not necessarily with designing learning algorithms.Gain in-depth knowledge of the TensorFlow API and primitives.Understand how to train and tune machine learning systems with TensorFlow on large datasets.Learn how to use TensorFlow with convolutional networks, recurrent networks, LSTMs, and reinforcement learning.
With this practical guide, you'll learn how Kudu's architecture and features solve a unique problem in the Hadoop ecosystem. If you're familiar with other storage layer projects such HDFS, HBase, Spanner, and Cassandra, you'll quickly learn-and appreciate-the unique contribution Kudu makes to this ecosystem.
Challenges us to step back and take an objective look at the technology driving our lives. The author illustrates that we're forgetting one important thing - our Selves, the human spirit from which technology stems. He examines the deceiving virtues of technology - how we're killing education, socializing our machines, and mechanizing our society.
In this practical book, two expert product managers provide straightforward guidance for people looking to join the thriving enterprise market. Authors Blair Reeves and Benjamin Gaines explain critical differences between enterprise and consumer products, and deliver strategies for overcoming challenges when building for the enterprise.
Deep learning doesnt have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, youll learn how to solve deep-learning problems for classifying and generating text, images, and music.Each chapter consists of several recipes needed to complete a single project, such as training a music recommending system. Author Douwe Osinga also provides a chapter with half a dozen techniques to help you if youre stuck. Examples are written in Python with code available on GitHub as a set of Python notebooks.Youll learn how to:Create applications that will serve real usersUse word embeddings to calculate text similarityBuild a movie recommender system based on Wikipedia linksLearn how AIs see the world by visualizing their internal stateBuild a model to suggest emojis for pieces of textReuse pretrained networks to build an inverse image search serviceCompare how GANs, autoencoders and LSTMs generate iconsDetect music styles and index song collections
Prenumerera på vårt nyhetsbrev för att få fantastiska erbjudanden och inspiration för din nästa läsning.
Genom att registrera dig accepterar du vår personuppgiftspolicy.
