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Getting Started with Containers in Google Cloud Platform: Deploy, Manage, and Secure Containerized Applications
by Shimon IfrahDeploy, manage, and secure containers and containerized applications on Google Cloud Platform (GCP). This book covers each container service in GCP from the ground up and teaches you how to deploy and manage your containers on each service.You will start by setting up and configuring GCP tools and the tenant environment. You then will store and manage Docker container images with GCP Container Registry (ACR). Next, you will deploy containerized applications with GCP Cloud Run and create an automated CI/CD deployment pipeline using Cloud Build. The book covers GCP’s flagship service, Google Kubernetes Service (GKE), and deployment of a Kubernetes cluster using clear steps and considering GCP best practices using the GCP management console and gcloud command-line tool. Also covered is monitoring containers and containerized applications on GCP with Cloud Monitoring, and backup and restore containers and containerized applications on GCP.By the end of the book, you will know how to get started with GCP container services and understand the fundamentals of each service and the supporting services needed to run containers in a production environment. This book also assists you in transferring your skills from AWS and Azure to GCP using the knowledge you have acquired on each platform and leveraging it to gain more skills.What You Will LearnGet started with Google Cloud Platform (GCP)Store Docker images on GCP Container Registry Deploy Google Kubernetes Engine (GKE) clusterSecure containerized applications on GCPUse Cloud Build to deploy containers Use GCP Batch for batch job processing on Kubernetes Who This Book Is ForGoogle Cloud administrators, developers, and architects who want to get started and learn more about containers and containerized applications on Google Cloud Platform (GPC)
5G Mobile Core Network: Design, Deployment, Automation, and Testing Strategies
by Rajaneesh Sudhakar ShettyGet up to speed on 5G and prepare for the roll out of the next generation of mobile technology. The book begins with an introduction to 5G and the advanced features of 5G networks, where you’ll see what makes it bigger, better, and faster. You will learn 5G NSA and SA packet core design along with some design challenges, taking a practical approach towards design and deployment. Next, you will understand the testing of the 5G packet core and how to automate it. The book concludes with some advanced service provider strategies, including architectural considerations for service providers to enhance their network and provide services to non-public 5G networks.5G Mobile Core Network is intended for those who wish to understand 5G, and also for those who work extensively in a service provider environment either as operators or as vendors performing activities such as network design, deployment, testing, and automation of the network. By the end of this book you will be able to understand the benefits in terms of CAPEX and OPEX while considering one design over another. Consulting engineers will be able to evaluate the design options in terms of 5G use cases, the scale of deployment, performance, efficiency, latency, and other key considerations. What You Will Learn Understand the life cycle of a deployment right from pre-deployment phase to post-deployment phaseSee use cases of 5G and the various options to design, implement, and deploy themExamine the deployment of 5G networks to large-scale service providersDiscover the MVNO/MVNE strategies that a service provider can implement in 5GWho This Book Is For Anyone who is curious about 5G and wants to learn more about the technology.
Building Solutions with Microsoft Teams: Understanding the Teams App Developer Platform
by Jenkins NSExplore Microsoft Teams and use its principal tools such as Node.js, npm, Yeoman, Gulp, TypeScript, and React to help you develop for Teams better. This book covers the core components and use cases for Teams apps and guides you through ideas for automation, provisioning, and implementation. Building Solutions with Microsoft Teams starts with an overview of the Microsoft Teams developer platform followed by how to set up your environment for building apps and solutions with Teams. You will then go through various features of conversational bots and learn how to create a bot. You will gain an understanding of the messaging extension and command actions along with tabs for personal, groups, and teams contexts. Moving forward, you will work with SharePoint and Teams together via SharePoint Framework. Finally, you will manage the Teams life cycle and see design guidelines supported by various case studies. After reading this book, you will be able to integrate solutions from Power Apps, Power Automate, Power BI, and Power Virtual agents by using accelerators. You will also be able to leverage your existing skills from SharePoint Framework development. What You Will Learn Extend the Teams developer platform capabilitiesUnderstand Microsoft Graph, including lifecycle management, collaboration, calling, and online meetingsCreate an app package for your Microsoft Teams appConnect web services to Microsoft Teams with webhooks Who This Book Is ForMicrosoft Teams developers.
SQL Server 2019 AlwaysOn: Supporting 24x7 Applications with Continuous Uptime
by Peter A. CarterGet a fast start to using AlwaysOn, the SQL Server solution to high-availability and disaster recovery. This third edition is newly-updated to cover the 2019 editions of both SQL Server and Windows Server and includes strong coverage of implementing AlwaysOn Availability Groups on both Windows and Linux operating systems. The book provides a solid and accurate understanding of how to implement systems requiring consistent and continuous uptime, as well as how to troubleshoot those systems in order to keep them running and reliable. This edition is updated to account for all new major functionality and also includes coverage of implementing atypical configurations, such as clusterless and domain-independent Availability Groups, distributed Availability Groups, and implementing Availability Groups on Azure.The book begins with an introduction to high-availability and disaster recovery concepts such as Recovery Point Objectives (RPOs), Recovery Time Objectives (RTOs), availability levels, and the cost of downtime. You’ll then move into detailed coverage of implementing and configuring the AlwaysOn feature set in order to meet the business objectives set by your organization. Content includes coverage on implementing clusters, building AlwaysOn failover clustered instances, and configuring AlwaysOn Availability Groups.SQL Server 2019 AlwaysOn is chock full of real-world advice on how to build and configure the most appropriate topology to meet the high-availability and disaster recovery requirements you are faced with, as well as how to use AlwaysOn Availability Groups to scale-out read-only workloads. This is a practical and hands-on book to get you started quickly in using one of the most talked-about SQL Server feature sets. What You Will Learn Understand high availability and disaster recovery in SQL Server 2019Build and configure a Windows Cluster in Windows Server 2019Create and configure an AlwaysOn failover clustered instanceImplement AlwaysOn Availability Groups and appropriately configure themImplement AlwaysOn Availability Groups on Linux serversConfigure Availability Groups on Azure IaaSAdminister AlwaysOn technologies post implementationUnderstand typical configurations, such as clusterless and distributed Availability Groups Who This Book Is For For Microsoft SQL Server database administrators who interested in growing their knowledge and skills in SQL Server’s high-availability and disaster recovery feature set.
Building Custom Tasks for SQL Server Integration Services: The Power of .NET for ETL for SQL Server 2019 and Beyond
by Andy LeonardBuild custom SQL Server Integration Services (SSIS) tasks using Visual Studio Community Edition and C#. Bring all the power of Microsoft .NET to bear on your data integration and ETL processes, and for no added cost over what you’ve already spent on licensing SQL Server. New in this edition is a demonstration deploying a custom SSIS task to the Azure Data Factory (ADF) Azure-SSIS Integration Runtime (IR). All examples in this new edition are implemented in C#. Custom task developers are shown how to implement custom tasks using the widely accepted and default language for .NET development. Why are custom components necessary? Because even though the SSIS catalog of built-in tasks and components is a marvel of engineering, gaps remain in the available functionality. One such gap is a constraint of the built-in SSIS Execute Package Task, which does not allow SSIS developers to select SSIS packages from other projects in the SSIS Catalog. Examples in this book show how to create a custom Execute Catalog Package task that allows SSIS developers to execute tasks from other projects in the SSIS Catalog. Building on the examples and patterns in this book, SSIS developers may create any task to which they aspire, custom tailored to their specific data integration and ETL needs. What You Will LearnConfigure and execute Visual Studio in the way that best supports SSIS task developmentCreate a class library as the basis for an SSIS task, and reference the needed SSIS assembliesProperly sign assemblies that you create in order to invoke them from your taskImplement source code control via Azure DevOps, or your own favorite tool setTroubleshoot and execute custom tasks as part of your own projectsCreate deployment projects (MSIs) for distributing code-complete tasksDeploy custom tasks to Azure Data Factory Azure-SSIS IRs in the cloudCreate advanced editors for custom task parametersWho This Book Is ForFor database administrators and developers who are involved in ETL projects built around SQL Server Integration Services (SSIS). Readers do not need a background in software development with C#. Most important is a desire to optimize ETL efforts by creating custom-tailored tasks for execution in SSIS packages, on-premises or in ADF Azure-SSIS IRs.
Practical Ansible: Configuration Management from Start to Finish
by Vincent SestoGo from the basics of using Ansible to becoming proficient at implementing configuration management in your projects. This book uses a unique approach to teaching Ansible and configuration management while including realistic examples in its day-to-day use from server-based infrastructure to Amazon cloud-based deployments. Practical Ansible is separated into seven chapters that allow you to build your knowledge with each chapter, developing further as we move through the examples provided. It begins with the basics of Ansible, providing you with details on how to install and configure your environment while working with different Ansible modules from the command line. Next, it introduces you to working with Ansible tasks and organizing configuration code into playbooks. The book then shows you how to extend playbooks further, using roles and templates within the configuration code. Then, it extends your knowledge further by covering custom Ansible modules using Python and Linux shell scripts, and demonstrating how you can start to keep your secret values encrypted and secure using Ansible Vault. You’ll also extend Ansible roles with the use of Ansible Galaxy to reuse existing roles other users have created. The second half of the book moves configuration management to the Amazon cloud providing an introduction on what Amazon Web Services are, and how you can start to work with Ansible roles in AWS. The AWS examples use EC2 and CloudFormation services with Ansible template functions, Ansible Pull, and Ansible Git code deployment. The final part of the book includes a demonstration on how to use the numerous tools available to both Ansible and supporting libraries and modules to allow you to troubleshoot and test your configuration code before you deploy your changes to production systems. By the end of this book, you will have the skills for managing technology configuration management. You will be ready to work on real-world projects and be able to implement Ansible in your own technology projects. What You Will Learn Understand the basics of Ansible and how to install and configure the application on your systemMake changes to your system using Ansible directly in the command line using some of the more common Ansible modulesGroup your modules together as tasks in Ansible playbooks for more efficient deployment of configuration changesUse Ansible roles to help group and reuse configuration management changes and deploymentsSearch for community-created roles using Ansible Galaxy and how you can also host your own Ansible roles Deploy code to Amazon Web Services and how to utilize different AWS services in your deployment projectsUse external modules and libraries such as Molecule and Ansible Lint to help test your configurations before the configuration code is deployed Who This Book Is For System administrators, DevOps engineers, software engineers, and developers wanting to extend their current knowledge of computer systems and incorporate Ansible as a configuration management tool within them.
User-Driven Applications for Research and Science: Building Programs for Fields with Open Scenarios and Unpredictable User Actions
by Sergey AndreyevBuild programs that give users full control of their applications in order to meet end users' unique needs and scenarios. Over the last couple of decades, there has been an ongoing quandary in the developer world. Developers are enlisted to build applications to meet users’ demands; users get applications that meet the criteria from the developers’ point of view, but they are far from what the users envisioned. The difference is often wide and nearly catastrophic in fields where users’ actions are nearly impossible to predict, such as science, research work, financial analysis, and others. End users get frustrated with the applications because they were not built with their use cases in mind. For a long time, it was assumed that the developers who created the code should drive their programs and be responsible for all scenarios. While generally not an issue in simple programs, this view is wrong for complex applications in the field of science. These end users are the best specialists in their respective fields and need applications to work beyond the scenarios prepared and allowed for by developers.This book teaches you methods to manage your applications in a way that gives control to your target end users. You will learn proven methods using an easy and predictable instrument, the all-powerful algorithm, to create objects that are movable and re-sizable by users.Get ready to learn by example, using an algorithm of total movability and experience, implemented in different situations. You will begin with the simplest code examples and work your way up to real, complicated programs applicable in STEM fields.What You Will Learn Pass the control of your programs from developers to end usersUnderstand that the most valuable result is not the algorithm itself, but the consequence of using itBuild user-driven applications that include total movability of screen elementsSee concepts applied in real situations and scenariosBe exposed to well-known programs and tasks for developing user-driven applicationsAccess accompanying code written in C# and available on GitHub Who This Book Is ForDevelopers who want to write or design programs that give their target end users full control over their application
High Performance SQL Server: Consistent Response for Mission-Critical Applications
by Benjamin NevarezDesign and configure SQL Server instances and databases in support of high-throughput, mission-critical applications providing consistent response times in the face of variations in numbers of users and query volumes. In this new edition, with over 100 pages of additional content, every original chapter has been updated for SQL Server 2019, and the book also includes two new chapters covering SQL Server on Linux and Intelligent Query Processing. This book shows you how to configure SQL Server and design your databases to support a given instance and workload. You will learn advanced configuration options, in-memory technologies, storage and disk configuration, and more, all aimed toward enabling your desired application performance and throughput. Configuration doesn’t stop with implementation. Workloads change over time, and other impediments can arise to thwart desired performance. High Performance SQL Server covers monitoring and troubleshooting to aid you in detecting and fixing production performance problems and minimizing application outages. You will learn about a variety of tools, ranging from the traditional wait analysis methodology to the query store or indexing, and you will learn how improving performance is an iterative process. This book is an excellent complement to query performance tuning books and provides the other half of what you need to know by focusing on configuring the instances on which mission-critical queries are executed.What You Will LearnUnderstand SQL Server's database engine and how it processes queriesConfigure instances in support of high-throughput applicationsProvide consistent response times to varying user numbers and query volumesDesign databases for high-throughput applications with focus on performanceRecord performance baselines and monitor SQL Server instances against themTroubleshot and fix performance problemsWho This Book Is ForSQL Server database administrators, developers, and data architects. The book is also of use to system administrators who are managing and are responsible for the physical servers on which SQL Server instances are run.
Kubernetes: Preparing for the CKA and CKAD Certifications
by Philippe MartinMaster all the concepts and tools necessary to start administering a Kubernetes cluster and deploying applications to production. You will cover the entire curricula of the two Kubernetes certifications (for application developers and administrators).The initial chapters guide you through deployment of a Kubernetes cluster on virtual machines and explore the different components of the control plane. Next, you will work with the kubectl command-line tool; namespaces, labels, selectors, and annotations—common resources used through the Kubernetes API. The following chapters describe the principle of controllers and detail how workload controllers work as well as the possibilities for configuring deployed applications. You will also learn how to deploy a scalable and self-healing application, how pods are scheduled to nodes, how parts of the application can communicate, and how the application is discoverable from the outside. Next, you will cover security concerns describing the different authentication methods, the RBAC authorization mode, security contexts, network policies, and how to secure container images. You will also cover using persistent volumes for your containers to store long-term data, monitoring your clusters and applications and implementing design patterns for multi-container pods. The concluding chapters guide you through the upgrade of your deployed cluster.After reading this book, you will have enough knowledge to deploy a complex application using a Kubernetes cluster and be ready for the certification exams.What You Will LearnDeploy a Kubernetes cluster with kubeadm and learn how the control plane worksDiscover how the Kubernetes API is structuredDeploy secure, auto-scaled, and self-healing applicationsMaster the kubectl command-line toolWho This Book Is For Administrators and application developers with good knowledge of micro-services development and deployment.
Pro SQL Server Relational Database Design and Implementation: Best Practices for Scalability and Performance
by Louis DavidsonLearn effective and scalable database design techniques in SQL Server 2019 and other recent SQL Server versions. This book is revised to cover additions to SQL Server that include SQL graph enhancements, in-memory online transaction processing, temporal data storage, row-level security, and other design-related features. This book will help you design OLTP databases that are high-quality, protect the integrity of your data, and perform fast on-premises, in the cloud, or in hybrid configurations. Designing an effective and scalable database using SQL Server is a task requiring skills that have been around for well over 30 years, using technology that is constantly changing. This book covers everything from design logic that business users will understand to the physical implementation of design in a SQL Server database. Grounded in best practices and a solid understanding of the underlying theory, author Louis Davidson shows you how to "get it right" in SQL Server database design and lay a solid groundwork for the future use of valuable business data.What You Will LearnDevelop conceptual models of client data using interviews and client documentationImplement designs that work on premises, in the cloud, or in a hybrid approachRecognize and apply common database design patternsNormalize data models to enhance integrity and scalability of your databases for the long-term use of valuable dataTranslate conceptual models into high-performing SQL Server databasesSecure and protect data integrity as part of meeting regulatory requirementsCreate effective indexing to speed query performanceUnderstand the concepts of concurrencyWho This Book Is ForProgrammers and database administrators of all types who want to use SQL Server to store transactional data. The book is especially useful to those wanting to learn the latest database design features in SQL Server 2019 (features that include graph objects, in-memory OLTP, temporal data support, and more). Chapters on fundamental concepts, the language of database modeling, SQL implementation, and the normalization process lay a solid groundwork for readers who are just entering the field of database design. More advanced chapters serve the seasoned veteran by tackling the latest in physical implementation features that SQL Server has to offer. The book has been carefully revised to cover all the design-related features that are new in SQL Server 2019.
Applied Data Science Using PySpark: Learn the End-to-End Predictive Model-Building Cycle
by Ramcharan Kakarla Sundar Krishnan Sridhar AllaDiscover the capabilities of PySpark and its application in the realm of data science. This comprehensive guide with hand-picked examples of daily use cases will walk you through the end-to-end predictive model-building cycle with the latest techniques and tricks of the trade. Applied Data Science Using PySpark is divided unto six sections which walk you through the book. In section 1, you start with the basics of PySpark focusing on data manipulation. We make you comfortable with the language and then build upon it to introduce you to the mathematical functions available off the shelf. In section 2, you will dive into the art of variable selection where we demonstrate various selection techniques available in PySpark. In section 3, we take you on a journey through machine learning algorithms, implementations, and fine-tuning techniques. We will also talk about different validation metrics and how to use them for picking the best models. Sections 4 and 5 go through machine learning pipelines and various methods available to operationalize the model and serve it through Docker/an API. In the final section, you will cover reusable objects for easy experimentation and learn some tricks that can help you optimize your programs and machine learning pipelines. By the end of this book, you will have seen the flexibility and advantages of PySpark in data science applications. This book is recommended to those who want to unleash the power of parallel computing by simultaneously working with big datasets. What You Will Learn Build an end-to-end predictive modelImplement multiple variable selection techniquesOperationalize modelsMaster multiple algorithms and implementations Who This Book is For Data scientists and machine learning and deep learning engineers who want to learn and use PySpark for real-time analysis of streaming data.
Deep Reinforcement Learning in Unity: With Unity ML Toolkit
by Abhilash MajumderGain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity.This book starts with an introduction to state-based reinforcement learning algorithms involving Markov models, Bellman equations, and writing custom C# code with the aim of contrasting value and policy-based functions in reinforcement learning. Then, you will move on to path finding and navigation meshes in Unity, setting up the ML Agents Toolkit (including how to install and set up ML agents from the GitHub repository), and installing fundamental machine learning libraries and frameworks (such as Tensorflow). You will learn about: deep learning and work through an introduction to Tensorflow for writing neural networks (including perceptron, convolution, and LSTM networks), Q learning with Unity ML agents, and porting trained neural network models in Unity through the Python-C# API. You will also explore the OpenAI Gym Environment used throughout the book.Deep Reinforcement Learning in Unity provides a walk-through of the core fundamentals of deep reinforcement learning algorithms, especially variants of the value estimation, advantage, and policy gradient algorithms (including the differences between on and off policy algorithms in reinforcement learning). These core algorithms include actor critic, proximal policy, and deep deterministic policy gradients and its variants. And you will be able to write custom neural networks using the Tensorflow and Keras frameworks. Deep learning in games makes the agents learn how they can perform better and collect their rewards in adverse environments without user interference. The book provides a thorough overview of integrating ML Agents with Unity for deep reinforcement learning.What You Will Learn Understand how deep reinforcement learning works in gamesGrasp the fundamentals of deep reinforcement learning Integrate these fundamentals with the Unity ML Toolkit SDKGain insights into practical neural networks for training Agent Brain in the context of Unity ML AgentsCreate different models and perform hyper-parameter tuningUnderstand the Brain-Academy architecture in Unity ML AgentsUnderstand the Python-C# API interface during real-time training of neural networksGrasp the fundamentals of generic neural networks and their variants using TensorflowCreate simulations and visualize agents playing games in Unity Who This Book Is ForReaders with preliminary programming and game development experience in Unity, and those with experience in Python and a general idea of machine learning
Practical Linux with Raspberry Pi OS: Quick Start
by Ashwin PajankarQuickly start programming with Linux while learning the Raspberry Pi OS—the Linux distribution designed specifically for low-cost Raspberry Pis. This short guide reviews Linux commands, GUI, and shell scripting in a holistic manner by diving into both advanced and day-to-day tasks using the Raspberry Pi OS.You'll comfortably work with the Linux command prompt, and explore the RPi OS GUI and all its base applications. Then move into writing your own programs with shell-programming and using high-level languages such as C, C++, and Python 3. You’ll also study hardware and GPIO programming. Use Python 3 for GPIO programming to drive LEDs and pushbuttons.Examples are written in Shell, C, C++, and Python 3. Graphical output is displayed in helpful screenshots that capture just what you’ll see when working in this environment. All code examples are well tested on actual Raspberry Pi boards. After reading this book and following the examples, you’ll be able to write programs for demonstration in your academic/industrial research work, business environment, or just your circle of friends for fun! What You'll LearnNavigate the core aspects of Linux and programming on a Linux platform Install Raspberry Pi OS on a Raspberry PiProgram in Shell, C, C++, and PythonRedirect Io and work with the crontabWho This Book Is ForLinux enthusiasts, software engineers, researchers, business analysts, and managers working with the low-cost Raspberry Pi.
Applied Neural Networks with TensorFlow 2: API Oriented Deep Learning with Python
by Orhan Gazi YalçınImplement deep learning applications using TensorFlow while learning the “why” through in-depth conceptual explanations. You’ll start by learning what deep learning offers over other machine learning models. Then familiarize yourself with several technologies used to create deep learning models. While some of these technologies are complementary, such as Pandas, Scikit-Learn, and Numpy—others are competitors, such as PyTorch, Caffe, and Theano. This book clarifies the positions of deep learning and Tensorflow among their peers. You'll then work on supervised deep learning models to gain applied experience with the technology. A single-layer of multiple perceptrons will be used to build a shallow neural network before turning it into a deep neural network. After showing the structure of the ANNs, a real-life application will be created with Tensorflow 2.0 Keras API. Next, you’ll work on data augmentation and batch normalization methods. Then, the Fashion MNIST dataset will be used to train a CNN. CIFAR10 and Imagenet pre-trained models will be loaded to create already advanced CNNs. Finally, move into theoretical applications and unsupervised learning with auto-encoders and reinforcement learning with tf-agent models. With this book, you’ll delve into applied deep learning practical functions and build a wealth of knowledge about how to use TensorFlow effectively. What You'll Learn Compare competing technologies and see why TensorFlow is more popularGenerate text, image, or sound with GANsPredict the rating or preference a user will give to an itemSequence data with recurrent neural networks Who This Book Is For Data scientists and programmers new to the fields of deep learning and machine learning APIs.
Quantum Computing Solutions: Solving Real-World Problems Using Quantum Computing and Algorithms
by Bhagvan KommadiKnow how to use quantum computing solutions involving artificial intelligence (AI) algorithms and applications across different disciplines.Quantum solutions involve building quantum algorithms that improve computational tasks within quantum computing, AI, data science, and machine learning. As opposed to quantum computer innovation, quantum solutions offer automation, cost reduction, and other efficiencies to the problems they tackle.Starting with the basics, this book covers subsystems and properties as well as the information processing network before covering quantum simulators. Solutions such as the Traveling Salesman Problem, quantum cryptography, scheduling, and cybersecurity are discussed in step-by-step detail. The book presents code samples based on real-life problems in a variety of industries, such as risk assessment and fraud detection in banking. In pharma, you will look at drug discovery and protein-folding solutions. Supply chain optimization and purchasing solutions are presented in the manufacturing domain. In the area of utilities, energy distribution and optimization problems and solutions are explained. Advertising scheduling and revenue optimization solutions are included from media and technology verticals. What You Will Learn Understand the mathematics behind quantum computingKnow the solution benefits, such as automation, cost reduction, and efficienciesBe familiar with the quantum subsystems and properties, including states, protocols, operations, and transformationsBe aware of the quantum classification algorithms: classifiers, and support and sparse support vector machinesUse AI algorithms, including probability, walks, search, deep learning, and parallelism Who This Book Is For Developers in Python and other languages interested in quantum solutions. The secondary audience includes IT professionals and academia in mathematics and physics. A tertiary audience is those in industry verticals such as manufacturing, banking, and pharma.
Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit
by Santanu PattanayakQuickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particles. It also examines Quantum machine learning, which can help solve some of the most challenging problems in forecasting, financial modeling, genomics, cybersecurity, supply chain logistics, cryptography among others.You'll start by reviewing the fundamental concepts of Quantum Computing, such as Dirac Notations, Qubits, and Bell state, followed by postulates and mathematical foundations of Quantum Computing. Once the foundation base is set, you'll delve deep into Quantum based algorithms including Quantum Fourier transform, phase estimation, and HHL (Harrow-Hassidim-Lloyd) among others. You'll then be introduced to Quantum machine learning and Quantum deep learning-based algorithms, along with advanced topics of Quantum adiabatic processes and Quantum based optimization. Throughout the book, there are Python implementations of different Quantum machine learning and Quantum computing algorithms using the Qiskit toolkit from IBM and Cirq from Google Research.What You'll LearnUnderstand Quantum computing and Quantum machine learningExplore varied domains and the scenarios where Quantum machine learning solutions can be appliedDevelop expertise in algorithm development in varied Quantum computing frameworksReview the major challenges of building large scale Quantum computers and applying its various techniquesWho This Book Is ForMachine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning
The TYPO3 Guidebook: Understand and Use TYPO3 CMS
by Felicity Brand Heather McNamee Jeffrey A. McGuireLearn how to make the most of TYPO3 – the enterprise CMS – to organize information and digital assets, and communicate globally with powerful multi-site and multilingual support. This book will show you how the TYPO3 CMS backend and frontend work from top to bottom. Content management is a core aspect of every company’s communications, whether intranets and internal digital asset repositories or public-facing product pages and online communities. The book starts with four chapters covering how TYPO3 works, giving you a high-level overview of the most important aspects you should know about, including its community and professional ecosystem. If you’ve never seen TYPO3 before, you’ll learn how to make the most of it and what makes TYPO3 different from other content management systems you may have used before. You'll then move on to 10 hands-on guides. These step-by-step tutorials show you how to work with TYPO3 CMS. Each guide is self-contained, introducing a scenario, and showing you how to solve a given problem. The guides include references to documentation, examples, code samples, and everything you need to get the job done. The TYPO3 Guidebook will help you learn how to put your creative ideas online with TYPO3. What You'll Learn Scope, plan, design, and build efficient websites and web applications with TYPO3Determine how TYPO3 can work best for you and how to avoid complicationsImplement a project from idea to launchManage client expectations and complete TYPO3 projects on time and within budgetUnderstand TYPO3 terminology in practical termsCreate TYPO3 projects using best practices and configure them efficientlyBuild integrations and features using TYPO3 Core APIs Who This Book is For Decision makers, project managers, consultants and developers
Modern Web Performance Optimization: Methods, Tools, and Patterns to Speed Up Digital Platforms
by Shailesh Kumar ShivakumarWeb-based platforms have become vehicles for enterprises to realize their digital strategy and are key to positive user engagement. The performance of these platforms can make the difference between an effective sale and a negative review. There exist several tools and methodologies to enhance your digital platform’s performance, and Modern Web Performance Optimization has arrived to walk you through them with an expert’s guidance. Author Shailesh Kumar Shivakumar breaks the study of web performance optimization down into four digestible, applicable dimensions: performance patterns, framework and methods, process and tools, and the modern web. This multi-faceted approach ensures a broad optimization of your platforms and avoids the typical pitfalls of neglecting essential steps that so many often do. Shivakumar analyzes web performance ecosystem components such as validation, governance, metrics, key performance indicators, assessments, and monitoring, just to name a few. The book discusses reference architectures and relevant tools and technologies for successfully implementing a best practices–driven solution. Modern web frameworks such as HTML5 and PWA are also covered. Modern Web Performance Optimization puts readers from any level of experience at ease. Accessible templates, real-world case studies, and your very own performance optimization checklist make this book an engaging and interactive learning opportunity for platform owners across industries. Developers, engineers, project managers, and more are set up for long-term success with Modern Web Performance Optimization at their fingertips. What You Will LearnAnalyze the performance optimization across end-to-end layersUtilize a comprehensive web optimization framework for digital projectsImplement proven methods, best practices, and tools for web performance optimization Who This Book Is ForSystem administrators, front-end developers, professionals looking to understand how to optimize their online presence
Cyber Security on Azure: An IT Professional’s Guide to Microsoft Azure Security
by Marshall Copeland Matthew JacobsPrevent destructive attacks to your Azure public cloud infrastructure, remove vulnerabilities, and instantly report cloud security readiness. This book provides comprehensive guidance from a security insider's perspective.Cyber Security on Azure supports cloud security operations and cloud security architects by supplying a path to clearly identify potential vulnerabilities to business assets and reduce security risk in Microsoft Azure subscription. This updated edition explores how to “lean-in” and recognize challenges with IaaS and PaaS for identity, networks, applications, virtual machines, databases, and data encryption to use the variety of Azure security tools. You will dive into Azure Cloud Security to guide cloud operations teams to become more security focused in many areas and laser focused on security configuration. New chapters cover Azure Kubernetes Service and Container security and you will get up and running quickly with an overview of Azure Sentinel SIEM Solution.What You'll LearnUnderstand enterprise privileged identity and security policies"Shift left" with security controls in Microsoft AzureConfigure intrusion detection and alertsReduce security risks using Azure Security ServiceWho This Book Is ForIT, cloud, and security administrators in Azure
Blockchain Enabled Applications: Understand the Blockchain Ecosystem and How to Make it Work for You
by Vikram Dhillon David Metcalf Max HooperLearn all about blockchain and its applications in cryptocurrency, healthcare, Internet of Things, finance, decentralized organizations, and more. Featuring case studies and practical insights, this book covers a unique mix of topics and offers insight into how to overcome hurdles that arise as the market and consumers grow accustomed to blockchain-based organizations and services. The book is divided into three major sections. The first section provides a historical background to blockchain technology. You will start with a historical context to financial capital markets when Bitcoin was invented, followed by mining protocols, the need for consensus, hardware mining, etc. Next, a formal introduction to blockchain is provided covering transaction workflow, role of decentralized network, and payment verification. Then, we dive deep into a different implementation of a blockchain: Ethereum. The main technical features, such as Ethereum Virtual Machine, are presented along with the smart contract programming language, Solidity. In this second section, you will look at some modern use cases for blockchain from a decentralized autonomous organization, high-performance computing in Ethereum and off-grid computations, and healthcare and scientific discovery. The final section of the book looks toward the future of blockchain. This is followed by chapters covering the rise of consortia in the blockchain world, the Hyperledger project, particularly the updates since 2018, and a chapter on educational blockchain games. This is followed by updates to EOS.IO, Chain Core, and Quorum, ICOs and a look at the major changes to financial markets brought about by blockchain and decentralized networks. What You Will Learn Get an overview of the popular games employed to teach the basic concepts of blockchain and decentralized networksBe familiar with the rise of blockchain consortiums as well as updates to Hyperledger Project, 2020Find out about cloud blockchains, including Microsoft Azure and Amazon Webservices, and how to set up test environmentsStudy machine learning integration in the blockchain and the role of smart contracts Who This Book Is For Blockchain developers interested in keeping up with the newest updates and students looking for a broad overview of this vast ecosystem, plus business executives who want to make informed product decisions about including blockchain as well as policy makers who want a better understanding of the current use cases
Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes
by Arjun PanesarThis updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things.You will understand how machine learning can be used to develop health intelligence–with the aim of improving patient health, population health, and facilitating significant care-payer cost savings.What You Will LearnUnderstand key machine learning algorithms and their use and implementation within healthcareImplement machine learning systems, such as speech recognition and enhanced deep learning/AIManage the complexities of massive dataBe familiar with AI and healthcare best practices, feedback loops, and intelligent agentsWho This Book Is ForHealth care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.
ML.NET Revealed: Simple Tools for Applying Machine Learning to Your Applications
by Sudipta MukherjeeGet introduced to ML.NET, a new open source, cross-platform machine learning framework from Microsoft that is intended to democratize machine learning and enable as many developers as possible.Dive in to learn how ML.NET is designed to encapsulate complex algorithms, making it easy to consume them in many application settings without having to think about the internal details. You will learn about the features that do the necessary “plumbing” that is required in a variety of machine learning problems, freeing up your time to focus on your applications. You will understand that while the infrastructure pieces may at first appear to be disconnected and haphazard, they are not. Developers who are curious about trying machine learning, yet are shying away from it due to its perceived complexity, will benefit from this book. This introductory guide will help you make sense of it all and inspire you to try out scenarios and code samples that can be used in many real-world situations.What You Will LearnCreate a machine learning model using only the C# languageBuild confidence in your understanding of machine learning algorithms Painlessly implement algorithms Begin using the ML.NET library softwareRecognize the many opportunities to utilize ML.NET to your advantageApply and reuse code samples from the bookUtilize the bonus algorithm selection quick references available onlineWho This Book Is ForDevelopers who want to learn how to use and apply machine learning to enrich their applications
Deploy Machine Learning Models to Production: With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform
by Pramod SinghBuild and deploy machine learning and deep learning models in production with end-to-end examples.This book begins with a focus on the machine learning model deployment process and its related challenges. Next, it covers the process of building and deploying machine learning models using different web frameworks such as Flask and Streamlit. A chapter on Docker follows and covers how to package and containerize machine learning models. The book also illustrates how to build and train machine learning and deep learning models at scale using Kubernetes.The book is a good starting point for people who want to move to the next level of machine learning by taking pre-built models and deploying them into production. It also offers guidance to those who want to move beyond Jupyter notebooks to training models at scale on cloud environments. All the code presented in the book is available in the form of Python scripts for you to try the examples and extend them in interesting ways.What You Will LearnBuild, train, and deploy machine learning models at scale using KubernetesContainerize any kind of machine learning model and run it on any platform using DockerDeploy machine learning and deep learning models using Flask and Streamlit frameworksWho This Book Is ForData engineers, data scientists, analysts, and machine learning and deep learning engineers
Beginning MLOps with MLFlow: Deploy Models in AWS SageMaker, Google Cloud, and Microsoft Azure
by Sridhar Alla Suman Kalyan AdariIntegrate MLOps principles into existing or future projects using MLFlow, operationalize your models, and deploy them in AWS SageMaker, Google Cloud, and Microsoft Azure. This book guides you through the process of data analysis, model construction, and training.The authors begin by introducing you to basic data analysis on a credit card data set and teach you how to analyze the features and their relationships to the target variable. You will learn how to build logistic regression models in scikit-learn and PySpark, and you will go through the process of hyperparameter tuning with a validation data set. You will explore three different deployment setups of machine learning models with varying levels of automation to help you better understand MLOps. MLFlow is covered and you will explore how to integrate MLOps into your existing code, allowing you to easily track metrics, parameters, graphs, and models. You will be guided through the process of deploying and querying your models with AWS SageMaker, Google Cloud, and Microsoft Azure. And you will learn how to integrate your MLOps setups using Databricks. What You Will Learn Perform basic data analysis and construct models in scikit-learn and PySparkTrain, test, and validate your models (hyperparameter tuning)Know what MLOps is and what an ideal MLOps setup looks likeEasily integrate MLFlow into your existing or future projectsDeploy your models and perform predictions with them on the cloud Who This Book Is ForData scientists and machine learning engineers who want to learn MLOps and know how to operationalize their models
Ontologies with Python: Programming OWL 2.0 Ontologies with Python and Owlready2
by Lamy Jean-BaptisteUse ontologies in Python, with the Owlready2 module developed for ontology-oriented programming. You will start with an introduction and refresher on Python and OWL ontologies. Then, you will dive straight into how to access, create, and modify ontologies in Python. Next, you will move on to an overview of semantic constructs and class properties followed by how to perform automatic reasoning. You will also learn about annotations, multilingual texts, and how to add Python methods to OWL classes and ontologies. Using medical terminologies as well as direct access to RDF triples is also covered. Python is one of the most used programming languages, especially in the biomedical field, and formal ontologies are also widely used. However, there are limited resources for the use of ontologies in Python. Owlready2, downloaded more than 60,000 times, is a response to this problem, and this book is the first one on the topic of using ontologies with Python.What You Will LearnUse Owlready2 to access and modify OWL ontologies in PythonPublish ontologies on dynamic websitesPerform automatic reasoning in PythonUse well-known ontologies, including DBpedia and Gene Ontology, and terminological resources, such as UMLS (Unified Medical Language System)Integrate Python methods in OWL ontologies Who Is This Book ForBeginner to experienced readers from biomedical sciences and artificial intelligence fields would find the book useful.