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Infrastructure as Code with Azure Bicep: Streamline Azure resource deployment by bypassing ARM complexities
by Yaser Adel Mehraban John Downs Edmondo RosiniThe ultimate guide to becoming proficient in Azure Bicep while having a better development experience and making your Infrastructure as Code seamless and error freeKey FeaturesLearn Azure Bicep from an official Microsoft trainerMaster the authoring experience to make your Infrastructure as Code journey seamlessGo beyond writing good templates with the help of advanced tips and tricksBook DescriptionIt's no secret that developers don't like using JSON files to declare their resources in Azure because of issues such as parameter duplication and not being able to use comments in templates. Azure Bicep helps resolve these issues, and this book will guide you, as a developer or DevOps engineer, to get the most out of the Bicep language.The book takes you on a journey from understanding Azure Resource Manager (ARM) templates and what their drawbacks are to how you can use Bicep to overcome them. You will get familiar with tools such as Visual Studio Code, the Bicep extension, the Azure CLI, PowerShell, Azure DevOps, and GitHub for writing reusable, maintainable templates. After that, you'll test the templates and deploy them to an Azure environment either from your own system or via a continuous integration and continuous delivery (CI/CD) pipeline. The book features a detailed overview of all the Bicep features, when to use what, and how to write great templates that fit well into your existing pipelines or in a new one. The chapters progress from easy to advanced topics and every effort has been put into making them easy to follow with examples, all of which are accessible via GitHub.By the end of this book, you'll have developed a solid understanding of Azure Bicep and will be able to create, test, and deploy your resources locally or in your CI/CD pipelines.What you will learnGet started with Azure Bicep and install the necessary toolsUnderstand the details of how to define resources with BicepUse modules to create templates for different teams in your companyOptimize templates using expressions, conditions, and loopsMake customizable templates using parameters, variables, and functionsDeploy templates locally or from Azure DevOps or GitHubStay on top of your IaC with best practices and industry standardsWho this book is forThis book is for cloud engineers, developers, and DevOps engineers who are responsible for writing templates to deploy resources in Microsoft Azure and contributing to CI/CD pipelines. Professionals who want to get started with DevOps and Infrastructure as Code when it comes to working with Microsoft Azure will also benefit from reading this book. Readers are expected to have a basic understanding of CI/CD concepts, must have worked with ARM templates to deploy resources to Azure, and must have used or be familiar with Azure DevOps or GitHub Actions for their CI/CD pipelines.
Machine Learning for Time-Series with Python: Forecast, predict, and detect anomalies with state-of-the-art machine learning methods
by Ben AuffarthBecome proficient in deriving insights from time-series data and analyzing a model's performanceKey FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time-series via real-world case studies on operations management, digital marketing, finance, and healthcareBook DescriptionMachine learning has emerged as a powerful tool to understand hidden complexities in time-series datasets, which frequently need to be analyzed in areas as diverse as healthcare, economics, digital marketing, and social sciences. These datasets are essential for forecasting and predicting outcomes or for detecting anomalies to support informed decision making.This book covers Python basics for time-series and builds your understanding of traditional autoregressive models as well as modern non-parametric models. You will become confident with loading time-series datasets from any source, deep learning models like recurrent neural networks and causal convolutional network models, and gradient boosting with feature engineering.Machine Learning for Time-Series with Python explains the theory behind several useful models and guides you in matching the right model to the right problem. The book also includes real-world case studies covering weather, traffic, biking, and stock market data.By the end of this book, you will be proficient in effectively analyzing time-series datasets with machine learning principles.What you will learnUnderstand the main classes of time-series and learn how to detect outliers and patternsChoose the right method to solve time-series problemsCharacterize seasonal and correlation patterns through autocorrelation and statistical techniquesGet to grips with time-series data visualizationUnderstand classical time-series models like ARMA and ARIMAImplement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning modelsBecome familiar with many libraries like Prophet, XGboost, and TensorFlowWho this book is forThis book is ideal for data analysts, data scientists, and Python developers who are looking to perform time-series analysis to effectively predict outcomes. Basic knowledge of the Python language is essential. Familiarity with statistics is desirable.
Artificial Intelligence with Power BI: Take your data analytics skills to the next level by leveraging the AI capabilities in Power BI
by Mary-Jo DiepeveenLearn how to create your own AI model and consume it in your Power BI reports to gain better insights from your dataKey FeaturesLearn how to gain better insights from your data by applying different AI techniques within Power BISave time by creating machine learning models independently and integrating them within your BI reportsUnderstand how to combine Cognitive Services and Azure Machine Learning together with Power BIBook DescriptionThe artificial intelligence (AI) capabilities in Power BI enable organizations to quickly and easily gain more intelligent insights from unstructured and structured data.This book will teach you how to make use of the many AI features available today in Power BI to quickly and easily enrich your data and gain better insights into patterns that can be found in your data.You'll begin by understanding the benefits of AI and how it can be used in Power BI. Next, you'll focus on exploring and preparing your data for building AI projects and then progress to using prominent AI features already available in Power BI, such as forecasting, anomaly detection, and Q&A. Later chapters will show you how to apply text analytics and computer vision within Power BI reports. This will help you create your own Q&A functionality in Power BI, which allows you to ask FAQs from another knowledge base and then integrate it with PowerApps. Toward the concluding chapters, you'll be able to create and deploy AutoML models trained in Azure ML and consume them in Power Query Editor. After your models have been trained, you'll work through principles such as privacy, fairness, and transparency to use AI responsibly.By the end of this book, you'll have learned when and how to enrich your data with AI using the out-of-the-box AI capabilities in Power BI.What you will learnApply techniques to mitigate bias and handle outliers in your dataPrepare time series data for forecasting in Power BIPrepare and shape your data for anomaly detectionUse text analytics in Power Query EditorIntegrate QnA Maker with PowerApps and create an appTrain your own models and identify the best one with AutoMLIntegrate an Azure ML workspace with Power BI and use endpoints to generate predictionsWho this book is forThis artificial intelligence BI book is for data analysts and BI developers who want to explore advanced analytics or artificial intelligence possibilities with their data. Prior knowledge of Power BI will help you get the most out of this book.
Kotlin Design Patterns and Best Practices: Build scalable applications using traditional, reactive, and concurrent design patterns in Kotlin, 2nd Edition
by Alexey Soshin Anton ArhipovImprove the scalability and maintainability of your applications by implementing a variety of design patterns using KotlinKey FeaturesUnderstand traditional and modern design patterns to improve the design of your applicationCombine the benefits of object-oriented, functional, reactive, and concurrent programmingChoose the best microservices architecture and frameworks for your web applicationBook DescriptionDesign patterns are well-known solutions to common architectural problems as they allow you to solve many problems efficiently and create a shared vocabulary between developers. This book shows you how easy it can be to implement traditional design patterns in the modern multi-paradigm Kotlin programming language, and takes you through the new patterns and paradigms that have emerged.This second edition is updated to cover the changes introduced from Kotlin 1.2 up to 1.5 and focuses more on the idiomatic usage of coroutines, which have become a stable language feature. You'll begin by learning about the practical aspects of smarter coding in Kotlin, and will understand basic Kotlin syntax and the impact of design patterns on your code.The book also provides an in-depth explanation of the classical design patterns, such as Creational, Structural, and Behavioral families, before moving on to functional programming. You'll go through reactive and concurrent patterns, and finally, get to grips with coroutines and structured concurrency to write performant, extensible, and maintainable code.By the end of this Kotlin book, you'll have explored the latest trends in architecture and design patterns for microservices, as well as understanding the tradeoffs when choosing between different architectures.What you will learnImplement all the classical design patterns using the Kotlin programming languageApply reactive and concurrent design patterns to make your application more scalableDiscover best practices in Kotlin and explore its new featuresUnderstand the key principles of functional programming and learn how they apply to KotlinFind out how to write idiomatic Kotlin code and learn which patterns to avoidHarness the power of Kotlin to design concurrent and reliable systems with easeCreate an effective microservice with Kotlin and the Ktor frameworkWho this book is forThis book is for developers looking to apply design patterns they've learned from other languages in Kotlin to build reliable, scalable, and maintainable applications. Prior programming knowledge is necessary to get started with this book. Experience in Java or design patterns is helpful, but not mandatory.
Crystal Programming: A project-based introduction to building efficient, safe, and readable web and CLI applications
by George Dietrich Guilherme BernalThe ultimate guide to Crystal programming covering all its fundamental concepts such as OOP and concurrent programming to help you write readable and safe code and build fast applicationsKey FeaturesThe book uses an example-based approach for a better demonstration of the underlying conceptsDevelop a thorough appreciation of the roles of the macro API and annotationsLeverage supportive tools – spec, documentation, deployment, and automationBook DescriptionCrystal is a programming language with a concise and user-friendly syntax, along with a seamless system and a performant core, reaching C-like speed. This book will help you gain a deep understanding of the fundamental concepts of Crystal and show you how to apply them to create various types of applications.This book comes packed with step-by-step explanations of essential concepts and practical examples. You'll learn how to use Crystal's features to create complex and organized projects relying on OOP and its most common design patterns. As you progress, you'll gain a solid understanding of both the basic and advanced features of Crystal. This will enable you to build any application, including command-line interface (CLI) programs and web applications using IOs, concurrency and C bindings, HTTP servers, and the JSON API.By the end of this programming book, you'll be equipped with the skills you need to use Crystal programming for building and understanding any application you come across.What you will learnExplore how Crystal combines the merits of other languagesUnderstand how to leverage existing C libraries without writing any CFocus on zero-cost abstractions with compile-time macrosUse an example-based approach to demonstrate language featuresDevelop a variety of Crystal applications, such as web and CLI appsGain an understanding of the macro API and annotationsWho this book is forDevelopers who want to learn Crystal programming or anyone looking to improve their ability to solve real-world problems using the language will find this book helpful. Experience in application development using any other programming language is expected. However, prior knowledge of Crystal is not required.
Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
by Sebastian Raschka Vahid Mirjalili Yuxi (Hayden) Liu Dmytro DzhulgakovThis book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch's simple to code frameworkKey FeaturesLearn applied machine learning with a solid foundation in theoryClear, intuitive explanations take you deep into the theory and practice of Python machine learningFully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practicesBook DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself.Why PyTorch?PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric.You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP).This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learnExplore frameworks, models, and techniques for machines to 'learn' from dataUse scikit-learn for machine learning and PyTorch for deep learningTrain machine learning classifiers on images, text, and moreBuild and train neural networks, transformers, and boosting algorithmsDiscover best practices for evaluating and tuning modelsPredict continuous target outcomes using regression analysisDig deeper into textual and social media data using sentiment analysisWho this book is forIf you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource.Written for developers and data scientists who want to create practical machine learning with Python and PyTorch deep learning code. This Python book is ideal for anyone who wants to teach computers how to learn from data.Working knowledge of the Python programming language, along with a good understanding of calculus and linear algebra is a must.
Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
by Sebastian Raschka Vahid Mirjalili Yuxi (Hayden) LiuThis book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework. Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesLearn applied machine learning with a solid foundation in theoryClear, intuitive explanations take you deep into the theory and practice of Python machine learningFully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practicesBook DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself. Why PyTorch? PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP). This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learnExplore frameworks, models, and techniques for machines to learn from dataUse scikit-learn for machine learning and PyTorch for deep learningTrain machine learning classifiers on images, text, and moreBuild and train neural networks, transformers, and boosting algorithmsDiscover best practices for evaluating and tuning modelsPredict continuous target outcomes using regression analysisDig deeper into textual and social media data using sentiment analysisWho this book is forIf you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch. Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.
Python Web Development with Sanic: An in-depth guide for Python web developers to improve the speed and scalability of web applications
by Adam HopkinsBuild a performant and scalable web application using Sanic, along with maintaining clean code to fit your unique challenges and business requirementsKey FeaturesExpand your knowledge of web application architecture for building scalable web appsLearn the core philosophies of performance and scalability from one of the creators of SanicCreate a complete Python web app from scratch and learn to translate the knowledge you gain across various use casesBook DescriptionToday's developers need something more powerful and customizable when it comes to web app development. They require effective tools to build something unique to meet their specific needs, and not simply glue a bunch of things together built by others. This is where Sanic comes into the picture. Built to be unopinionated and scalable, Sanic is a next-generation Python framework and server tuned for high performance.This Sanic guide starts by helping you understand Sanic's purpose, significance, and use cases. You'll learn how to spot different issues when building web applications, and how to choose, create, and adapt the right solution to meet your requirements. As you progress, you'll understand how to use listeners, middleware, and background tasks to customize your application. The book will also take you through real-world examples, so you will walk away with practical knowledge and not just code snippets.By the end of this web development book, you'll have gained the knowledge you need to design, build, and deploy high-performance, scalable, and maintainable web applications with the Sanic framework.What you will learnUnderstand the difference between WSGI, Async, and ASGI serversDiscover how Sanic organizes incoming data, why it does it, and how to make the most of itImplement best practices for building reliable, performant, and secure web appsExplore useful techniques for successfully testing and deploying a Sanic web appCreate effective solutions for the modern web, including task management, bot integration, and GraphQLIdentify security concerns and understand how to deal with them in your Sanic appsWho this book is forThis book is for Python web developers who have basic to intermediate-level knowledge of how web technologies work and are looking to take their applications to the next level using the power of the Sanic framework. Working knowledge of Python web development along with frameworks such as Django and/or Flask will be helpful but is not required. A basic to intermediate-level understanding of Python 3, HTTP, RESTful API patterns, and modern development practices and tools, such as type annotations, pytest, and virtual environments will also be beneficial.
Practical Finite Element Simulations with SOLIDWORKS 2022: An illustrated guide to performing static analysis with SOLIDWORKS Simulation
by Khameel B. MustaphaHarness the power of SOLIDWORKS Simulation for design, assembly, and performance analysis of componentsKey FeaturesUnderstand the finite element simulation concepts with the help of case studies and detailed explanationsDiscover the features of various SOLIDWORKS element typesPerform structural analysis with isotropic and composite material properties under a variety of loading conditionsBook DescriptionSOLIDWORKS is a dominant computer-aided design (CAD) software for the 3D modeling, designing, and analysis of components. This book helps you get to grips with SOLIDWORKS Simulation, which is a remarkable and integral part of SOLIDWORKS predominantly deployed for advanced product performance assessment and virtual prototyping.With this book, you'll take a hands-on approach to learning SOLIDWORKS Simulation with the help of step-by-step guidelines on various aspects of the simulation workflow. You'll begin by learning about the requirements for effective simulation of parts and components, along with the idealization of physical components and their representation with finite element models. As you progress through the book, you'll find exercises at the end of each chapter, and you'll be able to download the geometry models used in all the chapters from GitHub. Finally, you'll discover how to set up finite element simulations for the static analysis of components under various types of loads, and with different types of materials, from simple isotropic to composite, and different boundary conditions.By the end of this SOLIDWORKS 2022 book, you'll be able to conduct basic and advanced static analyses with SOLIDWORKS Simulation and have practical knowledge of how to best use the family of elements in the SOLIDWORKS Simulation library.What you will learnRun static simulations with truss, beam, shell, and solid element typesDemonstrate static simulations with mixed elementsAnalyze components with point loads, torsional loads, transverse distributed loads, surface pressure loads, and centrifugal speedExplore the analysis of components with isotropic and composite materialsAnalyze members under thermo-mechanical and cyclic loadsDiscover how to minimize simulation errors and perform convergence analysisAcquire practical knowledge of plane elements to reduce computational overheadWho this book is forThis book is for engineers and analysts working in the field of aerospace, mechanical, civil, and mechatronics engineering who are looking to explore the simulation capabilities of SOLIDWORKS. Basic knowledge of modeling in SOLIDWORKS or any CAD software is assumed.
Policy Design in the Age of Digital Adoption: Explore how PolicyOps can drive Policy as Code adoption in an organization's digital transformation
by Ricardo FerreiraA proven methodology to build a PolicyOps function and public policy design frameworks for digital adoption, supporting your organization's journey into new paradigms and service models such as Cloud, SaaS, CaaS, FaaS, and DevOpsKey FeaturesUnderstand and define policies that can be consumed across the businessLeverage a framework to embed Policy as Code into the organizationLearn how to use Open Policy Agent and its powerful policy language, RegoBook DescriptionPolicy as Code (PaC) is a powerful paradigm that enables organizations to implement, validate, and measure policies at scale. Policy Design in the Age of Digital Adoption is a comprehensive guide to understanding policies, their design, and implementation for cloud environments using a DevOps-based framework. You'll discover how to create the necessary automation, its integration, and which stakeholders to involve.Complete with essential concepts, practical examples, and self-assessment questions, this book will help you understand policies and how new technologies such as cloud, microservices, and serverless leverage Policy as Code. You'll work with a custom framework to implement PaC in the organization, and advance to integrating policies, guidelines, and regulations into code to enhance the security and resilience posture of the organization. You'll also examine existing tools, evaluate them, and learn a framework to implement PaC so that technical and business teams can collaborate more effectively.By the end of this book, you'll have gained the confidence to design digital policies across your organizational environment.What you will learnUnderstand policies, guidelines, regulations and how they fit together in an organizationDiscover policy-related current challenges brought by digital transformation regarding policiesFind out about Open Policy Engine (OPA) and other policy engines for different environmentsGet to grips with the latest developments in PaC through a review of the literature, toolset, and usageExplore the PaC framework to develop trust at scale, leveraging patterns and best practicesBecome familiar with tool evaluation and selection using real-world examplesWho this book is forFrom decision-makers, such as chief information officers (CIOs) and chief information security officers (CISOs) responsible for affecting change horizontally in an organization, to cloud and DevOps architects and engineers, this book will help professionals involved in designing, implementing, and measuring policies in their organizations. A basic understanding of concepts such as cloud-native technologies, Infrastructure as Code, DevOps, and automation is necessary to get started with this book.
WordPress Plugin Development Cookbook: Explore the complete set of tools to craft powerful plugins that extend the world's most popular CMS, 3rd Edition
by Yannick LefebvreCreate plugins for WordPress through detailed recipes that cover the creation of shortcodes, custom post types, and custom blocks, integrate data from external sources, and do much more with this recipe-based guideKey FeaturesCreate plugins that change and extend WordPress to perform virtually any taskExtend the WordPress Block Editor (Gutenberg) and other components with the help of detailed examples and explanationsCustomize WordPress to meet your project's needs and create plugins that benefit the entire communityBook DescriptionWordPress is one of the most widely used, powerful, and open content management systems (CMSs). Whether you're a site owner trying to find the right extension, a developer who wants to contribute to the community, or a website developer working to fulfill a client's needs, learning how to extend WordPress' capabilities will help you to unleash its full potential. This book will help you become familiar with API functions to create secure plugins with easy-to-use administration interfaces. This third edition contains new recipes and up-to-date code samples, including new chapters on creating custom blocks for the block editor and integrating data from external sources. From one chapter to the next, you'll learn how to create plugins of varying complexity, ranging from a few lines of code to complex extensions that provide intricate new capabilities. You'll start by using the basic mechanisms provided in WordPress to create plugins, followed by recipes covering how to design administration panels, enhance the post editor with custom fields, store custom data, and even create custom blocks. You'll safely incorporate dynamic elements into web pages using scripting languages, learn how to integrate data from external sources, and build new widgets that users will be able to add to WordPress sidebars and widget areas. By the end of this book, you will be able to create WordPress plugins to perform any task you can imagine.What you will learnDiscover action and filter hooks, which form the basis of plugin creationExplore the creation of administration pages and add new content management sections through custom post types and custom fieldsAdd new components to the block editor libraryFetch, cache, and regularly update data from external sourcesBring in external data sources to enhance your contentMake your pages dynamic by using JavaScript, jQuery, and AJAX and adding new widgets to the platformAdd support for plugin translation and distributing your work to the WordPress communityWho this book is forThis book is for WordPress users, developers, and site integrators interested in creating new plugins to address their personal needs, fulfill client requirements, and bring new capabilities to the WordPress community. Basic knowledge of PHP and WordPress is expected.
Simplifying Android Development with Coroutines and Flows: Learn how to use Kotlin coroutines and the flow API to handle data streams asynchronously in your Android app
by Jomar Tigcal Aileen Apolo-de JesusGet to grips with asynchronous programming in Android using simple, modern, and testable code through Kotlin coroutines and flowKey FeaturesFind out how to improve app performance with Kotlin coroutinesDiscover the new recommended ways to use Kotlin coroutines and flowsLearn the basics of asynchronous programming, along with an overview of coroutines and flowBook DescriptionCoroutines and flows are the new recommended way for developers to carry out asynchronous programming in Android using simple, modern, and testable code. This book will teach you how coroutines and flows work and how to use them in building Android applications, along with helping you to develop modern Android applications with asynchronous programming using real data. The book begins by showing you how to create and handle Kotlin coroutines on Android. You'll explore asynchronous programming in Kotlin, and understand how to test Kotlin coroutines. Next, you'll learn about Kotlin flows on Android, and have a closer look at using Kotlin flows by getting to grips with handling flow cancellations and exceptions and testing the flows. By the end of this book, you'll have the skills you need to build high-quality and maintainable Android applications using coroutines and flows.What you will learnUnderstand how coroutines and flows differ from existing waysApply asynchronous programming in Android with coroutines and flowsFind out how to build your own coroutines and flows in AndroidHandle, manipulate, and combine data in coroutines and flowsHandle cancellations and exceptions from coroutines and flowsDiscover how to add tests for your coroutines and flowsIntegrate coroutines and flows into your Android projectsWho this book is forThis book is for intermediate-level Android developers who want to level up their Android app-building skills. Familiarity with Android development and basic knowledge of Kotlin are needed to make the most of this book.
Distributed Machine Learning with Python: Accelerating model training and serving with distributed systems
by Guanhua WangBuild and deploy an efficient data processing pipeline for machine learning model training in an elastic, in-parallel model training or multi-tenant cluster and cloudKey FeaturesAccelerate model training and interference with order-of-magnitude time reductionLearn state-of-the-art parallel schemes for both model training and servingA detailed study of bottlenecks at distributed model training and serving stagesBook DescriptionReducing time cost in machine learning leads to a shorter waiting time for model training and a faster model updating cycle. Distributed machine learning enables machine learning practitioners to shorten model training and inference time by orders of magnitude. With the help of this practical guide, you'll be able to put your Python development knowledge to work to get up and running with the implementation of distributed machine learning, including multi-node machine learning systems, in no time. You'll begin by exploring how distributed systems work in the machine learning area and how distributed machine learning is applied to state-of-the-art deep learning models. As you advance, you'll see how to use distributed systems to enhance machine learning model training and serving speed. You'll also get to grips with applying data parallel and model parallel approaches before optimizing the in-parallel model training and serving pipeline in local clusters or cloud environments. By the end of this book, you'll have gained the knowledge and skills needed to build and deploy an efficient data processing pipeline for machine learning model training and inference in a distributed manner.What you will learnDeploy distributed model training and serving pipelinesGet to grips with the advanced features in TensorFlow and PyTorchMitigate system bottlenecks during in-parallel model training and servingDiscover the latest techniques on top of classical parallelism paradigmExplore advanced features in Megatron-LM and Mesh-TensorFlowUse state-of-the-art hardware such as NVLink, NVSwitch, and GPUsWho this book is forThis book is for data scientists, machine learning engineers, and ML practitioners in both academia and industry. A fundamental understanding of machine learning concepts and working knowledge of Python programming is assumed. Prior experience implementing ML/DL models with TensorFlow or PyTorch will be beneficial. You'll find this book useful if you are interested in using distributed systems to boost machine learning model training and serving speed.
Hands-On Visual Studio 2022: A developer's guide to exploring new features and best practices in VS2022 for maximum productivity
by Miguel Angel Garcia Hector Uriel RojasLearn to design, develop, debug, and deploy technologies by harnessing the full power of Visual Studio 2022 by discovering its new features and exclusive techniquesKey FeaturesDiscover solutions to common problems faced while using Visual Studio 2022Explore tips, tricks, and best practices and discover ways to overcome source-code challengesDeep dive into Visual Studio's new features and unleash its potential to enhance your coding journeyBook DescriptionVisual Studio 2022 is the complete and ideal integrated development environment (IDE) for creating large, complex, and scalable applications. It is one of the most complete tools available for development, especially with Microsoft technologies.This book will teach you how to take advantage of the tools available with this IDE to write clean code faster. You'll begin by learning how to set up and start Visual Studio 2022 and how to use all the tools provided by this IDE. You will then explore key combinations, tips, and additional utilities that can help you to code faster and review your code constantly. Next, you will see how to compile, debug, and inspect your project to analyze its current behavior using Visual Studio. The book also shows you how to insert reusable blocks of code writing simple statements. Later, you will learn about visual aids and artificial intelligence that will help you improve productivity and understand what is going on in the project.By the end of this book, you will be able to set up your development environment using Visual Studio 2022, personalize the tools and layout, and use shortcuts and extensions to improve your productivity.What you will learnUnderstand what's new in Visual Studio 2022Discover the various code tools to improve productivityExplore the benefits of using .NET 6 in Visual Studio 2022Perform compilation, debugging, and version control comfortablyBecome well-versed with various shortcuts, tricks, tips, and tools to improve productivity within Visual Studio 2022Implement remote and collaborative work with Visual Studio 2022Who this book is forThis book is for .NET software developers focusing on web development and web developers who want to learn about the new features, tools, and features available in Visual Studio 2022. Basic knowledge of HTML, CSS, and JavaScript or frameworks such as React and Angular is assumed.
Python Machine Learning Workbook for Beginners: 10 Machine Learning Projects Explained from Scratch
by AI Sciences OUA practical guide to machine learning with Python through the presentation and guided completion of ten real-world projectsKey FeaturesStep-by-step roadmap to data science and machine learningA Python crash course in machine learning10 machine learning and data science projects for practical studyBook DescriptionMachine Learning (ML) is the lifeblood of businesses worldwide. ML tools empower organizations to identify profitable opportunities fast and help them to better understand potential risks. The ever-expanding data, cost-effective data storage, and competitively priced powerful processing continue to drive the growth of ML. This is the best time you could enter the exciting machine learning universe. Industries are reinventing themselves constantly by developing more advanced data analysis models. These models analyze larger and more complex data than ever while delivering instantaneous and more accurate results on enormous scales. In this backdrop, it is evident that hands-on practice is everything in machine learning. Tons of theory will amount to nothing if you don't have enough hands-on practice. Textbooks and online classes mislead you into a false sense of mastery. The easy availability of learning resources tricks you and you become overconfident. But when you try to apply the theoretical concepts you have learned, you realize it's not that simple. This is where projects play a crucial role in your learning journey. Projects are doubtless the best investment of your time. You'll not only enjoy learning but you'll also make quick progress. And unlike studying boring theoretical concepts, you'll find that working on projects is easier to stay motivated. The projects in this book cover ten different interesting topics. Each project will help you refine your ML skills and apply them in the real world. These projects also present you with an opportunity to enrich your portfolio, making it simpler to find a great job, explore interesting career paths, and even negotiate a higher pay package. Overall, this learning-by-doing book will help you accomplish your machine learning career goals faster. The code bundle for this course is available at https://www.aispublishing.net/ai-sciences-bookWhat you will learnHouse price prediction using linear regressionFiltering spam email messages using Naive Bayes algorithmPredicting used car sale price using Feedforward Artificial Neural NetworksPredicting stock market trends with RNN (LSTM)Language translation using Seq2Seq encoder-decoder LSTMClassifying cats and dogs images using Convolutional Neural NetworksMovie recommender system using item-based collaborative filteringFace detection with OpenCV in PythonHandwritten English character recognition with CNNCustomer segmentation based on income and spendingWho this book is forThe scripts, images, and graphs are clear and provide visuals to the text description. If you're new to ML and self-study is your only option, then this book is a must.
Practical Autodesk AutoCAD 2023 and AutoCAD LT 2023: A beginner's guide to 2D drafting and 3D modeling with Autodesk AutoCAD, 2nd Edition
by Jaiprakash Pandey Yasser ShoukryLearn 2D drawing and 3D modeling from scratch using AutoCAD and AutoCAD LT 2023 and become a CAD professionalKey FeaturesLearn techniques for making, modifying, and managing AutoCAD 2D and 3D drawingsUnderstand how to use reusable and named objects like blocks, xRef, and layersScale, annotate, and print drawings from model space and layoutBook DescriptionAutoCAD is one of the most versatile software applications for architectural and engineering designs and the most popular computer-aided design (CAD) platform for 2D drafting and 3D modeling. This hands-on 2nd edition guide will take you through everything you need to know to make the most out of this powerful tool, from a simple tour of the user interface to using advanced tools.Starting with basic drawing shapes and functions, you'll get to grips with the fundamentals of CAD designs. You'll then learn about effective drawing management using layers, dynamic blocks, and groups, and discover how to add annotations and plots like a professional. As you progress, the book will show you how to convert your 2D drawings into 3D models and shapes. You'll also discover advanced features, such as isometric drawings, drawing utilities for managing and recovering complex files, quantity surveying, and multidisciplinary drawing files using xRefs. Finally, you'll focus on rendering and visualizing your designs in AutoCAD.By the end of this book, you'll have developed a solid understanding of CAD principles and be able to work with AutoCAD software confidently to build impressive 2D and 3D creations.What you will learnUnderstand CAD fundamentals like functions, navigation, and componentsCreate complex 3D objects using primitive shapes and editing toolsWork with reusable objects like blocks and collaborate using xRefExplore advanced features like external references and dynamic blocksDiscover surface and mesh modeling tools such as Fillet, Trim, and ExtendUse the paper space layout to create plots for 2D and 3D modelsConvert your 2D drawings into 3D modelsWho this book is forThis 3D modeling book is for design engineers, mechanical engineers, architects, and anyone working in construction, manufacturing, or similar fields. Whether you're an absolute beginner, student, or professional looking to upgrade your engineering design skills, you'll find this AutoCAD book useful. No prior knowledge of CAD or AutoCAD is necessary.
Advanced Python Programming: Accelerate your Python programs using proven techniques and design patterns, 2nd Edition
by Quan NguyenWrite fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge librariesKey FeaturesBenchmark, profile, and accelerate Python programs using optimization toolsScale applications to multiple processors with concurrent programmingMake applications robust and reusable using effective design patternsBook DescriptionPython's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages.In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level.This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models.The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming.You'll also understand the common problems that cause undesirable behavior in concurrent programs.Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable.By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.What you will learnWrite efficient numerical code with NumPy, pandas, and XarrayUse Cython and Numba to achieve native performanceFind bottlenecks in your Python code using profilersOptimize your machine learning models with JAXImplement multithreaded, multiprocessing, and asynchronous programsSolve common problems in concurrent programming, such as deadlocksTackle architecture challenges with design patternsWho this book is forThis book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects.
SQL for Data Analytics: Harness the power of SQL to extract insights from data, 3rd Edition
by Jun Shan Matt Goldwasser Upom Malik Benjamin JohnstonTake your first steps to becoming a fully qualified data analyst by learning how to explore complex datasetsKey FeaturesMaster each concept through practical exercises and activitiesDiscover various statistical techniques to analyze your dataImplement everything you've learned on a real-world case study to uncover valuable insightsBook DescriptionEvery day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace. This book helps you analyze this data and identify key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. SQL for Data Analytics, Third Edition is a great way to get started with data analysis, showing how to effectively sort and process information from raw data, even without any prior experience. You will begin by learning how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of your current dataset. You will also discover how to work with advanced data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you will be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation. By the end of this book, you will be proficient in the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.What you will learnUse SQL to clean, prepare, and combine different datasetsAggregate basic statistics using GROUP BY clausesPerform advanced statistical calculations using a WINDOW functionImport data into a database to combine with other tablesExport SQL query results into various sourcesAnalyze special data types in SQL, including geospatial, date/time, and JSON dataOptimize queries and automate tasksThink about data problems and find answers using SQLWho this book is forIf you're a database engineer looking to transition into analytics or a backend engineer who wants to develop a deeper understanding of production data and gain practical SQL knowledge, you will find this book useful. This book is also ideal for data scientists or business analysts who want to improve their data analytics skills using SQL.Basic familiarity with SQL (such as basic SELECT, WHERE, and GROUP BY clauses) as well as a good understanding of linear algebra, statistics, and PostgreSQL 14 are necessary to make the most of this SQL data analytics book.
Exploring Deepfakes: Deploy powerful AI techniques for face replacement and more with this comprehensive guide
by Bryan Lyon Matt ToraMaster the innovative world of deepfakes and generative AI for face replacement with this full-color guidePurchase of the print or Kindle book includes a free PDF eBookKey FeaturesUnderstand what deepfakes are, their history, and how to use the technology ethicallyGet well-versed with the workflow and processes involved to create your own deepfakesLearn how to apply the lessons and techniques of deepfakes to your own problemsBook DescriptionApplying Deepfakes will allow you to tackle a wide range of scenarios creatively.Learning from experienced authors will help you to intuitively understand what is going on inside the model. You'll learn what deepfakes are and what makes them different from other machine learning techniques, and understand the entire process from beginning to end, from finding faces to preparing them, training the model, and performing the final swap.We'll discuss various uses for face replacement before we begin building our own pipeline. Spending some extra time thinking about how you collect your input data can make a huge difference to the quality of the final video. We look at the importance of this data and guide you with simple concepts to understand what your data needs to really be successful.No discussion of deepfakes can avoid discussing the controversial, unethical uses for which the technology initially became known. We'll go over some potential issues, and talk about the value that deepfakes can bring to a variety of educational and artistic use cases, from video game avatars to filmmaking.By the end of the book, you'll understand what deepfakes are, how they work at a fundamental level, and how to apply those techniques to your own needs.What you will learnGain a clear understanding of deepfakes and their creationUnderstand the risks of deepfakes and how to mitigate themCollect efficient data to create successful deepfakesGet familiar with the deepfakes workflow and its stepsExplore the application of deepfakes methods to your own generative needsImprove results by augmenting data and avoiding overtrainingExamine the future of deepfakes and other generative AIsUse generative AIs to increase video content resolutionWho this book is forThis book is for AI developers, data scientists, and anyone looking to learn more about deepfakes or techniques and technologies from Deepfakes to help them generate new image data. Working knowledge of Python programming language and basic familiarity with OpenCV, Pillow, Pytorch, or Tensorflow is recommended to get the most out of the book.
Quantum Machine Learning and Optimisation in Finance: On the Road to Quantum Advantage
by Antoine Jacquier Alexander Lipton Oleksiy Kondratyev Marcos Lopez PradoLearn the principles of quantum machine learning and how to apply them in finance.Purchase of the print or Kindle book includes a free eBook in the PDF format.Key FeaturesDiscover how to solve optimisation problems on quantum computers that can provide a speedup edge over classical methodsUse methods of analogue and digital quantum computing to build powerful generative modelsCreate the latest algorithms that work on Noisy Intermediate-Scale Quantum (NISQ) computersBook DescriptionWith recent advances in quantum computing technology, we finally reached the era of Noisy Intermediate-Scale Quantum (NISQ) computing. NISQ-era quantum computers are powerful enough to test quantum computing algorithms and solve hard real-world problems faster than classical hardware.Speedup is so important in financial applications, ranging from analysing huge amounts of customer data to high frequency trading. This is where quantum computing can give you the edge. Quantum Machine Learning and Optimisation in Finance shows you how to create hybrid quantum-classical machine learning and optimisation models that can harness the power of NISQ hardware.This book will take you through the real-world productive applications of quantum computing. The book explores the main quantum computing algorithms implementable on existing NISQ devices and highlights a range of financial applications that can benefit from this new quantum computing paradigm.This book will help you be one of the first in the finance industry to use quantum machine learning models to solve classically hard real-world problems. We may have moved past the point of quantum computing supremacy, but our quest for establishing quantum computing advantage has just begun!What you will learnTrain parameterised quantum circuits as generative models that excel on NISQ hardwareSolve hard optimisation problemsApply quantum boosting to financial applicationsLearn how the variational quantum eigensolver and the quantum approximate optimisation algorithms workAnalyse the latest algorithms from quantum kernels to quantum semidefinite programmingApply quantum neural networks to credit approvalsWho this book is forThis book is for Quants and developers, data scientists, researchers, and students in quantitative finance. Although the focus is on financial use cases, all the methods and techniques are transferable to other areas.
Salesforce Data Architect Certification Guide: Comprehensive coverage of the Salesforce Data Architect exam content to help you pass on the first attempt
by Aaron AllportLearn data architecture essentials and prepare for the Salesforce Certified Data Architect exam with the help of tips and mock test questionsKey FeaturesLeverage data modelling, Salesforce database design, and techniques for effective data designLearn master data management, Salesforce data management, and how to include considerationsGet to grips with large data volumes, performance tuning, and poor performance mitigation techniquesBook DescriptionThe Salesforce Data Architect is a prerequisite exam for the Application Architect half of the Salesforce Certified Technical Architect credential. This book offers complete, up-to-date coverage of the Salesforce Data Architect exam so you can take it with confidence.The book is written in a clear, succinct way with self-assessment and practice exam questions, covering all the topics necessary to help you pass the exam with ease. You'll understand the theory around Salesforce data modeling, database design, master data management (MDM), Salesforce data management (SDM), and data governance. Additionally, performance considerations associated with large data volumes will be covered. You'll also get to grips with data migration and understand the supporting theory needed to achieve Salesforce Data Architect certification.By the end of this Salesforce book, you'll have covered everything you need to know to pass the Salesforce Data Architect certification exam and have a handy, on-the-job desktop reference guide to re-visit the concepts.What you will learnUnderstand the topics relevant to passing the Salesforce Data Architect examExplore specialist areas, such as large data volumesTest your knowledge with the help of exam-like questionsPick up useful tips and tricks that can be referred to time and againUnderstand the reasons underlying the way Salesforce data management worksDiscover the techniques that are available for loading massive amounts of dataWho this book is forThis book is for both aspiring Salesforce data architects and those already familiar with Salesforce data architecture who want to pass the exam and have a reference guide to revisit the material as part of their day-to-day job. Working knowledge of the Salesforce platform is assumed, alongside a clear understanding of Salesforce architectural concepts.
Mastering Microsoft Power BI: Expert techniques to create interactive insights for effective data analytics and business intelligence, 2nd Edition
by Brett Powell Greg DecklerPlan, design, develop, and manage robust Power BI solutions to generate meaningful insights and make data-driven decisionsKey FeaturesMaster the latest dashboarding and reporting features of Microsoft Power BICombine data from multiple sources, create stunning visualizations and publish Power BI apps to thousands of usersGet the most out of Microsoft Power BI with real-world use cases and examplesBook DescriptionMastering Microsoft Power BI, Second Edition, provides an advanced understanding of Power BI to get the most out of your data and maximize business intelligence. This updated edition walks through each essential phase and component of Power BI, and explores the latest, most impactful Power BI features. Using best practices and working code examples, you will connect to data sources, shape and enhance source data, and develop analytical data models. You will also learn how to apply custom visuals, implement new DAX commands and paginated SSRS-style reports, manage application workspaces and metadata, and understand how content can be staged and securely distributed via Power BI apps. Furthermore, you will explore top report and interactive dashboard design practices using features such as bookmarks and the Power KPI visual, alongside the latest capabilities of Power BI mobile applications and self-service BI techniques. Additionally, important management and administration topics are covered, including application lifecycle management via Power BI pipelines, the on-premises data gateway, and Power BI Premium capacity. By the end of this Power BI book, you will be confident in creating sustainable and impactful charts, tables, reports, and dashboards with any kind of data using Microsoft Power BI.What you will learnBuild efficient data retrieval and transformation processes with the Power Query M language and dataflowsDesign scalable, user-friendly DirectQuery, import, and composite data modelsCreate basic and advanced DAX measuresAdd ArcGIS Maps to create interesting data storiesBuild pixel-perfect paginated reportsDiscover the capabilities of Power BI mobile applicationsManage and monitor a Power BI environment as a Power BI administratorScale up a Power BI solution for an enterprise via Power BI Premium capacityWho this book is forBusiness Intelligence professionals and intermediate Power BI users looking to master Power BI for all their data visualization and dashboarding needs will find this book useful. An understanding of basic BI concepts is required and some familiarity with Microsoft Power BI will be helpful to make the most out of this book.
Kickstart Modern Android Development with Jetpack and Kotlin: Enhance your applications by integrating Jetpack and applying modern app architectural concepts
by Catalin GhitaExplore modern Android development in Kotlin 1.6.10 with this condensed hands-on guide to building reliable apps using libraries such as Compose, ViewModel, Hilt, Retrofit, Flow, and moreKey FeaturesExplore Jetpack libraries and other modern technologies for Android developmentImprove the architectural design of your Android appsEnhance the quality of your Android projects' code bases and applications using the latest librariesBook DescriptionWith Jetpack libraries, you can build and design high-quality, robust Android apps that have an improved architecture and work consistently across different versions and devices. This book will help you understand how Jetpack allows developers to follow best practices and architectural patterns when building Android apps while also eliminating boilerplate code. Developers working with Android and Kotlin will be able to put their knowledge to work with this condensed practical guide to building apps with the most popular Jetpack libraries, including Jetpack Compose, ViewModel, Hilt, Room, Paging, Lifecycle, and Navigation. You'll get to grips with relevant libraries and architectural patterns, including popular libraries in the Android ecosystem such as Retrofit, Coroutines, and Flow while building modern applications with real-world data. By the end of this Android app development book, you'll have learned how to leverage Jetpack libraries and your knowledge of architectural concepts for building, designing, and testing robust Android applications for various use cases.What you will learnIntegrate popular Jetpack libraries such as Compose, ViewModel, Hilt, and Navigation into real Android apps with KotlinApply modern app architecture concepts such as MVVM, dependency injection, and clean architectureExplore Android libraries such as Retrofit, Coroutines, and FlowIntegrate Compose with the rest of the Jetpack libraries or other popular Android librariesWork with other Jetpack libraries such as Paging and Room while integrating a real REST API that supports paginationTest Compose UI and the application logic through unit testsWho this book is forThis book is for junior and intermediate-level Android developers looking to level up their Android development skills to develop high-quality apps using Jetpack libraries and other cutting-edge technologies. Beginners with knowledge of Android development fundamentals will also find this book useful. Familiarity with Kotlin is assumed.
Data Preprocessing with Python for Absolute Beginners: Take your first steps in data preparation with Python
by AI Sciences OUThis book is dedicated to data preparation and explains how to perform different data preparation techniques on various datasets using different data preparation libraries written in the Python programming language.Key FeaturesA crash course in Python to fill any gaps in prerequisite knowledge and a solid foundation on which to build your new skillsA complete data preparation pipeline for your guided practiceThree real-world projects covering each major task to cement your learned skills in data preparation, classification, and regressionBook DescriptionThe book follows a straightforward approach. It is divided into nine chapters. Chapter 1 introduces the basic concept of data preparation and installation steps for the software that we will need to perform data preparation in this book. Chapter 1 also contains a crash course on Python, followed by a brief overview of different data types in Chapter 2. You will then learn how to handle missing values in the data, while the categorical encoding of numeric data is explained in Chapter 4.The second half of the course presents data discretization and describes the handling of outliers' process. Chapter 7 demonstrates how to scale features in the dataset. Subsequent chapters teach you to handle mixed and DateTime data type, balance data, and practice resampling. A full data preparation final project is also available at the end of the book.Different types of data preprocessing techniques have been explained theoretically, followed by practical examples in each chapter. Each chapter also contains an exercise that students can use to evaluate their understanding of the chapter's concepts. By the end of this course, you will have built a solid working knowledge in data preparation--the first steps to any data science or machine learning career and an essential skillset for any aspiring developer.The code bundle for this course is available at https://www.aispublishing.net/book-data-preprocessingWhat you will learnExplore different libraries for data preparationUnderstand data typesHandle missing dataEncode categorical dataDiscretize dataLearn to handle outliersPractice feature scalingHandle mixed and DateTime variables and imbalanced datasetsEmploy your new skills to complete projects in data preparation, classification, and regressionWho this book is forIn addition to beginners in data preparation with Python, this book can also be used as a reference manual by intermediate and experienced programmers. It contains data preprocessing code samples using multiple data visualization libraries.
How to Test a Time Machine: A practical guide to test architecture and automation
by Noemi Ferrera Joe ColantonioRev up your career with powerful project enhancements using this comprehensive guide to test architectures and methodologies applicable to every area of testingPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesExplore the full test architecture spectrumDiscover a range of challenging automation applications with real-world scenariosLearn with easy-to-follow start-up examples including DevOps for testing, AI, XR, and cloudBook DescriptionFrom simple websites to complex applications, delivering quality is crucial for achieving customer satisfaction. How to Test a Time Machine provides step-by-step explanations of essential concepts and practical examples to show you how you can leverage your company's test architecture from different points in the development life cycle.You'll begin by determining the most effective system for measuring and improving the delivery of quality applications for your company, and then learn about the test pyramid as you explore it in an innovative way. You'll also cover other testing topics, including cloud, AI, and VR for testing.Complete with techniques, patterns, tools, and exercises, this book will help you enhance your understanding of the testing process. Regardless of your current role within development, you can use this book as a guide to learn all about test architecture and automation and become an expert and advocate for quality assurance.By the end of this book, you'll be able to deliver high-quality applications by implementing the best practices and testing methodologies included in the book.What you will learnIdentify quality maturity levels and processes to step up your product qualityDevelop the ability to think outside the box when testing methodologiesExamine the various types of tests and their applications from an unconventional perspectiveUnderstand how to apply different technologies to the testing processPractice and polish your testing skills with practical code exercisesExpedite your career growth with quality assuranceWho this book is forThis book is for test owners, developers, managers, manual QAs, SDETS, team leads, and systems engineers who wish to get started or improve the current QA systems. Test owners looking for inspiration and out-of-the-box solutions for challenging issues will also find this book useful.