Learn to use mobile DevOps for faster, more efficient mobile development by uncovering the secrets of mobile application development lifecycleKey Features:Discover best practices and mobile DevOps tools for test automation, app releases, performance optimization, security, error tracking, and moreEnhance efficiency, speed, and quality of your development process with mobile DevOpsExplore mobile DevOps components like continuous integration, testing, deployment, and monitoringPurchase of the print or Kindle book includes a free PDF eBookBook Description:To build mobile apps, you need to understand mobile-first features, tools, and processes that help you build, test, and release robust apps faster and more efficiently. The multitude of challenges stemming from mobile development's inherent complexities, including native iOS and Android app creation, cross-platform frameworks, and the implementation of scalable architectures within extensive teams, collectively contribute to a substantial number of obstacles that can significantly prolong the release process.This book will help you understand and implement the best practices of mobile DevOps for continuous integration, testing, delivery, deployment, and monitoring. You'll explore different challenges faced by developers due to varied OSs, the unforgiving nature of mobile applications, and continuous updates to mobile phones and learn how to maneuver through these challenges. You'll also get to grips with the latest trends while discovering the potential future of mobile DevOps, with valuable insights and guidance about integrating mobile development teams into your organization.By the end of this book, you'll be well-equipped to successfully implement mobile DevOps and build fast, qualitative, and efficient mobile apps for your team or organization.What You Will Learn:Discover the principles, components, and concepts of mobile DevOpsDevelop a successful mobile CI/CD strategy in your organizationIdentify the tools and processes for mobile app release and distributionDevelop and release mobile applications efficiently and reliablyImplement continuous testing with mobile DevOpsLeverage Mobile DevSecOps to improve security, efficiency of your Mobile app development processUnderstand how Platform Engineering and IDP Teams can improve Developer Productivity in Mobile DevOpsIdentify and fix problems with mobile application performance and data usageWho this book is for:This book is for DevOps engineers looking to learn more about mobile DevOps to build effective processes for releasing mobile apps quickly and frequently. It's also an excellent resource for mobile developers, mobile release managers, mobile architects, mobile platform engineers, and QA engineers, involved in mobile app development. Familiarity with DevOps and mobile app challenges related to testing, releasing, and monitoring especially at scale is a prerequisite.
Gain practical knowledge and hands-on expertise in implementing Google Cloud Platform services and prepare to confidently pass the exam on your first attemptKey Features:Explore Google Cloud Platform services and operations in depthGain hands-on experience to effectively employ Google Cloud servicesReceive tailored guidance for Associate Cloud Engineer certification from Google expertsPurchase of the print or Kindle book includes a free PDF eBookBook Description:Google Cloud Platform (GCP) is a leading cloud provider, helping companies and users worldwide to solve the most challenging business issues. This book will teach cloud engineers working with GCP how to implement, configure, and secure cloud environment, and help students gain confidence in utilizing various GCP services.The book begins by introducing you to Google Cloud and the ACE exam, including various resources that can help you pass. The next set of chapters will help you explore the various compute options in Google Cloud, such as Google Kubernetes Engine and Google Compute Engine. As you advance, you'll gain a clear understanding of the essence of the cloud, including networking and storage, as well as the data analytics products that Google Cloud provides. The chapters also cover key topics such as monitoring, logging, diagnostics, and price estimation along with the most crucial of subjects, security, with a particular focus on identity and access management. Finally, you'll be given the chance to test your newfound knowledge with the help of two mock exams.By the end of this book, you'll have learned the difference between various Google Cloud Platform services, along with specific use cases, and be able to implement these services with the GCP console and command-line utilities.What You Will Learn:Grasp the key topics needed to achieve ACE certificationImport and export data to and from Google CloudImplement and configure various networking options in Google CloudDerive insights from data with Google Data AnalyticsGain knowledge and experience in monitoring and loggingTest yourself in various scenarios while reading the bookChoose the optimal options to manage your solution's dataWho this book is for:This book is for anyone preparing for Associate Cloud Engineer certification. It can be used by IT system administrators as well as DevOps and it will be most useful to cloud architects as it covers all areas of Google Cloud Platform. This guide is ideal for those who want to start working with Google Cloud, gain practical knowledge, and achieve certification.
Kickstart your emotion analysis journey with this step-by-step guide to data science successKey Features:Discover the inner workings of the end-to-end emotional analysis workflowExplore the use of various ML models to derive meaningful insights from dataHone your craft by building and tweaking complex emotion analysis models with practical projectsPurchase of the print or Kindle book includes a free PDF eBookBook Description:Artificial intelligence and machine learning are the technologies of the future, and this is the perfect time to tap into their potential and add value to your business. Machine Learning for Emotion Analysis in Python helps you employ these cutting-edge technologies in your customer feedback system and in turn grow your business exponentially.With this book, you'll take your foundational data science skills and grow them in the exciting realm of emotion analysis. By following a practical approach, you'll turn customer feedback into meaningful insights assisting you in making smart and data-driven business decisions.The book will help you understand how to preprocess data, build a serviceable dataset, and ensure top-notch data quality. Once you're set up for success, you'll explore complex ML techniques, uncovering the concepts of deep neural networks, support vector machines, conditional probabilities, and more. Finally, you'll acquire practical knowledge using in-depth use cases showing how the experimental results can be transformed into real-life examples and how emotion mining can help track short- and long-term changes in public opinion.By the end of this book, you'll be well-equipped to use emotion mining and analysis to drive business decisions.What You Will Learn:¿Distinguish between sentiment analysis and emotion analysisMaster data preprocessing and ensure high-quality inputExpand the use of data sources through data transformationDesign models that employ cutting-edge deep learning techniquesDiscover how to tune your models' hyperparametersExplore the use of naive Bayes, SVMs, DNNs, and transformers for advanced use casesPractice your newly acquired skills by working on real-world scenariosWho this book is for:This book is for data scientists and Python developers looking to gain insights into the customer feedback for their product, company, brand, governorship, and more. Basic knowledge of machine learning and Python programming is a must.
Build scalable and reliable data ecosystems using Data Mesh, Databricks Spark, and KafkaKey Features:Develop modern data skills used in emerging technologiesLearn pragmatic design methodologies such as Data Mesh and data lakehousesGain a deeper understanding of data governancePurchase of the print or Kindle book includes a free PDF eBookBook Description:Modern Data Architectures with Python will teach you how to seamlessly incorporate your machine learning and data science work streams into your open data platforms. You'll learn how to take your data and create open lakehouses that work with any technology using tried-and-true techniques, including the medallion architecture and Delta Lake.Starting with the fundamentals, this book will help you build pipelines on Databricks, an open data platform, using SQL and Python. You'll gain an understanding of notebooks and applications written in Python using standard software engineering tools such as git, pre-commit, Jenkins, and Github. Next, you'll delve into streaming and batch-based data processing using Apache Spark and Confluent Kafka. As you advance, you'll learn how to deploy your resources using infrastructure as code and how to automate your workflows and code development. Since any data platform's ability to handle and work with AI and ML is a vital component, you'll also explore the basics of ML and how to work with modern MLOps tooling. Finally, you'll get hands-on experience with Apache Spark, one of the key data technologies in today's market.By the end of this book, you'll have amassed a wealth of practical and theoretical knowledge to build, manage, orchestrate, and architect your data ecosystems.What You Will Learn:Understand data patterns including delta architectureDiscover how to increase performance with Spark internalsFind out how to design critical data diagramsExplore MLOps with tools such as AutoML and MLflowGet to grips with building data products in a data meshDiscover data governance and build confidence in your dataIntroduce data visualizations and dashboards into your data practiceWho this book is for:This book is for developers, analytics engineers, and managers looking to further develop a data ecosystem within their organization. While they're not prerequisites, basic knowledge of Python and prior experience with data will help you to read and follow along with the examples.
Leverage the power of Ansible to gain complete control over your systems and automate deployments along with implementing configuration changesKey Features:Orchestrate major cloud platforms such as OpenStack, AWS, and AzureUse Ansible to automate network devicesAutomate your containerized workload with Docker, Podman, or KubernetesPurchase of the print or Kindle book includes a free PDF eBookBook Description:Ansible empowers you to automate a myriad of tasks, including software provisioning, configuration management, infrastructure deployment, and application rollouts. It can be used as a deployment tool as well as an orchestration tool. While Ansible provides simple yet powerful features to automate multi-layer environments using agentless communication, it can also solve other critical IT challenges, such as ensuring continuous integration and continuous deployment (CI/CD) with zero downtime.In this book, you'll work with the latest release of Ansible and learn how to solve complex issues quickly with the help of task-oriented scenarios. You'll start by installing and configuring Ansible on Linux and macOS to automate monotonous and repetitive IT tasks and learn concepts such as playbooks, inventories, and roles. As you progress, you'll gain insight into the YAML syntax and learn how to port between Ansible versions. Additionally, you'll understand how Ansible enables you to orchestrate multi-layer environments such as networks, containers, and the cloud.By the end of this Ansible book, you'll be well versed in writing playbooks and other related Ansible code to overcome all your IT challenges, from infrastructure-as-a-code provisioning to application deployments and handling mundane day-to-day maintenance tasks.What You Will Learn:Explore the fundamentals of the Ansible frameworkUnderstand how collections enhance your automation effortsAvoid common mistakes and pitfalls when writing automation codeExtend Ansible by developing your own modules and pluginsContribute to the Ansible project by submitting your own codeFollow best practices for working with cloud environment inventoriesTroubleshoot issues triggered during Ansible playbook runsWho this book is for:This book is for DevOps engineers, administrators, or any IT professionals looking to automate IT tasks using Ansible. Prior knowledge of Ansible is not a prerequisite.
Discover ways to enhance your application's functionality through hands-on learning for designing, testing, securing, deploying, and maintaining production-ready APIs Key Features:Learn how to design, develop, test, and deploy modern APIs in JavaExplore techniques for optimizing API performance and handling errorsSecure your APIs with industry-standard authentication and authorization techniquesGet a free PDF eBook with the purchase of the print or Kindle bookBook Description:Spring is a powerful and widely adopted framework for building scalable and reliable web applications in Java, complemented by Spring Boot, a popular extension to the framework that simplifies the setup and configuration of Spring-based applications. This book is an in-depth guide to harnessing Spring 6 and Spring Boot 3 for web development, offering practical knowledge of building modern robust web APIs and services.The book covers a wide range of topics that are essential for API development, including RESTful web service fundamentals, Spring concepts, and API specifications. It also explores asynchronous API design, security, designing user interfaces, testing APIs, and the deployment of web services. In addition to its comprehensive coverage, this book offers a highly contextual real-world sample app that you can use as a reference for building different types of APIs for real-world applications. This sample app will lead you through the entire API development cycle, encompassing design and specification, implementation, testing, and deployment.By the end of this book, you'll have learned how to design, develop, test, and deploy scalable and maintainable modern APIs using Spring 6 and Spring Boot 3, along with best practices for bolstering the security and reliability of your applications and improving your application's overall functionality.What You Will Learn:Create enterprise-level APIs using Spring and JavaUnderstand and implement REST, gRPC, GraphQL, and asynchronous APIs for various purposesDevelop real-world web APIs and services, from design to deploymentExpand your knowledge of API specifications and implementation best practicesDesign and implement secure APIs with authorization and authenticationDevelop microservices-based solutions with workflow and orchestration enginesAcquire proficiency in designing and testing user interfaces for APIsImplement logging and tracing mechanisms in your services and APIsWho this book is for: This book is for novice Java programmers, computer science graduates, coding boot camp alumni, and newcomers to the realm of creating real-world web APIs and services. It is an invaluable resource for Java developers transitioning to web development, offering an all-encompassing introduction to web service development. If you possess knowledge of fundamental programming constructs, data structures, and algorithms in Java but lack practical web development experience, this book will serve as a bridge to cultivate the essential skills for entry into the role of a web developer.
Discover Unreal Engine 5's networking techniques to create scalable and fully functional multiplayer game experiencesKey Features- Design a captivating multiplayer game using networking techniques from this illustrated guide- Understand how to use the Unreal Engine networking system with C++ and Blueprints- Carefully plan and develop an online experience from start to finish- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionIf you're fascinated by the immersive gaming experiences that enable multiple users to engage in collaborative or competitive gameplay, this Unreal Engine 5 game development book is for you.In this book, you'll learn the foundational principles behind multiplayer games. Starting with a sample project, you'll learn how to set up a networked system and make it work. Once the prototype of the project is functional, you'll start adding game logic, including obstacles and AI opponents, to heighten the challenges and engagement, offering a captivating experience for players. Next, you'll learn how to debug and optimize the project, before finally deploying the game build and integrating it with cloud services such as the Epic Online Services system.By the end of this book, you'll have the confidence to develop and manage multiplayer experiences using the Unreal Engine environment, taking your newfound programming skills in your upcoming projects.What you will learn- Get to grips with the basics of multiplayer game development- Understand the main elements of a networked level- Explore Unreal multiplayer features such as replication, RPCs, relevancy, and roles- Debug and optimize code for improved game performance- Deploy the game on LAN or online platforms- Use Epic Online Services to elevate the player experienceWho this book is forIf you are a game programmer, particularly an Unreal Engine developer, with little or no knowledge of video game networking systems and a passion for multiplayer games, this book will help you explore the subject in depth. Developers skilled in other game engines will find this book useful for understanding the principles of the Unreal multiplayer system, however, basic knowledge of Unreal Engine and C++ is strongly recommended.Table of Contents- Getting Started with Multiplayer Game Development- Understanding Networking Basics- Testing the Multiplayer System with a Project Prototype- Setting Up Your First Multiplayer Environment- Managing Actors in a Multiplayer Environment- Replicating Properties Over the Network- Using Remote Procedure Calls (RPCs)- Introducing AI into a Multiplayer Environment- Extending AI Behaviors- Enhancing the Player Experience- Debugging a Multiplayer Game- Managing Multiplayer Sessions- Handling Data During a Session- Deploying Multiplayer Games- Adding Epic Online Services (EOS)
A modern guide for aspiring Linux administrators-from command line basics to enterprise featuresKey Features:Explore a Linux environment with a focus on networking, installation, configuration, and cloud managementBecome familiar with the command line, basic commands, and directoryLearn how to automate apps and infrastructure using ChefPurchase of the print or Kindle book includes a free PDF eBookBook Description:Linux system administration is an essential aspect of maintaining and managing Linux servers within an organization. The role of a Linux system administrator is pivotal in ensuring the smooth functioning and security of these servers, making it a critical job function for any company that relies on Linux infrastructure.This book is a comprehensive guide designed to help you build a solid foundation in Linux system administration. It takes you from the fundamentals of Linux to more advanced topics, encompassing key areas such as Linux system installation, managing user accounts and filesystems, networking fundamentals, and Linux security techniques. Additionally, the book delves into the automation of applications and infrastructure using Chef, enabling you to streamline and optimize your operations.For both newcomers getting started with Linux and professionals looking to enhance their skills, this book is an invaluable hands-on guide with a structured approach and concise explanations that make it an effective resource for quickly acquiring and reinforcing Linux system administration skills. With the help of this Linux book, you'll be able to navigate the world of Linux administration confidently to meet the demands of your role.What You Will Learn:Master the use of the command line and adeptly manage software packagesManage users and groups locally or by using centralized authenticationSet up, diagnose, and troubleshoot Linux networksUnderstand how to choose and manage storage devices and filesystemsImplement enterprise features such as high availability and automation toolsPick up the skills to keep your Linux system secureWho this book is for:This book is for anyone new to the IT sector or those looking to learn Linux for a career in administering Linux systems. Aspiring cloud professionals, helpdesk staff, application support engineers, application developers, researchers, educators, and students considering the use of Linux servers will find this book especially useful.
Master reproducible ML and DL models with Python and PyTorch to achieve high performance, explainability, and real-world successKey Features:Learn how to improve performance of your models and eliminate model biasesStrategically design your machine learning systems to minimize chances of failure in productionDiscover advanced techniques to solve real-world challengesPurchase of the print or Kindle book includes a free PDF eBookBook Description:Debugging Machine Learning Models with Python is a comprehensive guide that navigates you through the entire spectrum of mastering machine learning, from foundational concepts to advanced techniques. It goes beyond the basics to arm you with the expertise essential for building reliable, high-performance models for industrial applications. Whether you're a data scientist, analyst, machine learning engineer, or Python developer, this book will empower you to design modular systems for data preparation, accurately train and test models, and seamlessly integrate them into larger technologies.By bridging the gap between theory and practice, you'll learn how to evaluate model performance, identify and address issues, and harness recent advancements in deep learning and generative modeling using PyTorch and scikit-learn. Your journey to developing high quality models in practice will also encompass causal and human-in-the-loop modeling and machine learning explainability. With hands-on examples and clear explanations, you'll develop the skills to deliver impactful solutions across domains such as healthcare, finance, and e-commerce.What You Will Learn:Enhance data quality and eliminate data flawsEffectively assess and improve the performance of your modelsDevelop and optimize deep learning models with PyTorchMitigate biases to ensure fairnessUnderstand explainability techniques to improve model qualitiesUse test-driven modeling for data processing and modeling improvementExplore techniques to bring reliable models to productionDiscover the benefits of causal and human-in-the-loop modelingWho this book is for:This book is for data scientists, analysts, machine learning engineers, Python developers, and students looking to build reliable, high-performance, and explainable machine learning models for production across diverse industrial applications. Fundamental Python skills are all you need to dive into the concepts and practical examples covered. Whether you're new to machine learning or an experienced practitioner, this book offers a breadth of knowledge and practical insights to elevate your modeling skills.
Develop expertise in Azure to plan, guide, and lead a streamlined modernization process Key Features:Explore core Azure infrastructure technologies and solutionsAchieve smooth app migration and modernization goals with cloud designMaster Azure architecture and adopt it to scale your business globallyPurchase of the print or Kindle book includes a free PDF eBookBook Description:Azure for Decision Makers provides a comprehensive overview of the latest updates in cloud security, hybrid cloud and multi-cloud solutions, and cloud migration in Azure. This book is a must-have introduction to the Microsoft Azure cloud platform, demonstrating the substantial scope of digital transformation and innovation that can be achieved with Azure's capabilities.The first set of chapters will get you up to speed with Microsoft Azure's evolution before showing you how to integrate it into your existing IT infrastructure. Next, you'll gain practical insights into application migration and modernization, focusing mainly on migration planning, implementation, and best practices. Throughout the book, you'll get the information you need to spearhead a smooth migration and modernization process, detailing Azure infrastructure as a service (IaaS) deployment, infrastructure management, and key application architectures. The concluding chapters will help you to identify and incorporate best practices for cost optimization and management, Azure DevOps, and Azure automation.By the end of this book, you'll have learned how to lead end-to-end Azure operations for your organization and effectively cost-optimize your processes ¿ from the planning and cloud migration stage through to troubleshooting.What You Will Learn:Find out how to optimize business costs with AzureStrategize the migration of applications to the cloud with AzureSmooth out the deployment and running of Azure infrastructure servicesEffectively define roles, responsibilities, and governance frameworks in DevOpsMaximize the utility of Azure security fundamentals and best practicesAdopt best practices to make the most of your Azure deploymentWho this book is for:Azure for Decision Makers is for business and IT decision makers who want to choose the right technology solutions for their businesses and optimize their management processes. It'll help you develop expertise in operating and administering the Azure cloud. This book will also be useful for CIOs and CTOs looking to understand more about how IT can make their business infrastructure more efficient and easier to use, which will reduce friction within their organization. Knowledge of Azure is helpful, but not necessary to get the most out of this guide.
Begin your journey toward efficient data manipulation with this robust technical guide and enhance your aggregation skills while building efficient pipelines for a variety of tasksKey Features: Build effective aggregation pipelines for increased productivity and performanceSolve common data manipulation and analysis problems with the help of practical examplesLearn essential strategies to aggregate time series data in financial datasets and IoTPurchase of the print or Kindle book includes a free PDF eBookBook Description: Officially endorsed by MongoDB, Inc., Practical MongoDB Aggregations helps you unlock the full potential of the MongoDB aggregation framework, including the latest features of MongoDB 7.0. This book provides practical, easy-to-digest principles and approaches for increasing your effectiveness in developing aggregation pipelines, supported by examples for building pipelines to solve complex data manipulation and analytical tasks.This book is customized for developers, architects, data analysts, data engineers, and data scientists with some familiarity with the aggregation framework. It begins by explaining the framework's architecture and then shows you how to build pipelines optimized for productivity and scale.Given the critical role arrays play in MongoDB's document model, the book delves into best practices for optimally manipulating arrays. The latter part of the book equips you with examples to solve common data processing challenges so you can apply the lessons you've learned to practical situations. By the end of this MongoDB book, you'll have learned how to utilize the MongoDB aggregation framework to streamline your data analysis and manipulation processes effectively.What You Will Learn: Develop dynamic aggregation pipelines tailored to changing business requirementsMaster essential techniques to optimize aggregation pipelines for rapid data processingAchieve optimal efficiency for applying aggregations to vast datasets with effective sharding strategiesEliminate the performance penalties of processing data externally by filtering, grouping, and calculating aggregated values directly within the databaseUse pipelines to help you secure your data access and distributionWho this book is for: This book is for intermediate-level developers, architects, analysts, engineers, and data scientists who are interested in learning about aggregation capabilities in MongoDB. Working knowledge of MongoDB is needed to get the most out of this book.
Learn the foundations of business intelligence, sector trade-offs, organizational structures, and technology stacks while mastering coursework, certifications, and interview success strategiesPurchase of the print or Kindle book includes a free PDF eBookKey Features:Identify promising job opportunities and ideal entry point into BIBuild, design, implement, and maintain BI systems successfullyAce your BI interview with author's expert guidance on certifications, trainings, and coursesBook Description:Navigating the challenging path of a business intelligence career requires you to consider your expertise, interest, and skills. Business Intelligence Career Master Plan explores key skills like data modeling, visualization, warehousing, organizational structures, technology stacks, coursework, certifications, and interview advice, enabling you to make informed decisions about your BI journey.You'll start by assessing the different roles in BI and matching your skills and career with the tech stack. You'll then learn to build taxonomy and a data story using visualization types. Additionally, you'll explore the fundamentals of programming, frontend development, backend development, software development lifecycle, and project management, giving you a broad view of the end-to-end BI process. With the help of the author's expert advice, you'll be able to identify what subjects and areas of study are crucial and would add significant value to your skillset.By the end of this book, you'll be well-equipped to make an informed decision on which of the myriad paths to choose in your business intelligence journey based on your skillset and interests.What You Will Learn:Understand BI roles, roadmap, and technology stackAccelerate your career and land your first job in the BI industryBuild the taxonomy of various data sources for your organizationUse the AdventureWorks database and PowerBI to build a robust data modelCreate compelling data stories using data visualizationAutomate, templatize, standardize, and monitor systems for productivityWho this book is for:This book is for BI developers and business analysts who are passionate about data and are looking to advance their proficiency and career in business intelligence. While foundational knowledge of tools like Microsoft Excel is required, having a working knowledge of SQL, Python, Tableau, and major cloud providers such as AWS or GCP will be beneficial.
Discover all the essential design and architectural patterns in one place to help you rapidly build and deploy your modern data platform using AWS servicesKey FeaturesLearn to build modern data platforms on AWS using data lakes and purpose-built data servicesUncover methods of applying security and governance across your data platform built on AWSFind out how to operationalize and optimize your data platform on AWSPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMany IT leaders and professionals are adept at extracting data from a particular type of database and deriving value from it. However, designing and implementing an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, still poses a challenge.This book will help you explore end-to-end solutions to common data, analytics, and AI/ML use cases by leveraging AWS services. The chapters systematically take you through all the building blocks of a modern data platform, including data lakes, data warehouses, data ingestion patterns, data consumption patterns, data governance, and AI/ML patterns. Using real-world use cases, each chapter highlights the features and functionalities of numerous AWS services to enable you to create a scalable, flexible, performant, and cost-effective modern data platform.By the end of this book, you'll be equipped with all the necessary architectural patterns and be able to apply this knowledge to efficiently build a modern data platform for your organization using AWS services.What you will learnFamiliarize yourself with the building blocks of modern data architecture on AWSDiscover how to create an end-to-end data platform on AWSDesign data architectures for your own use cases using AWS servicesIngest data from disparate sources into target data stores on AWSBuild data pipelines, data sharing mechanisms, and data consumption patterns using AWS servicesFind out how to implement data governance using AWS servicesWho this book is forThis book is for data architects, data engineers, and professionals creating data platforms. The book's use case-driven approach helps you conceptualize possible solutions to specific use cases, while also providing you with design patterns to build data platforms for any organization. It's beneficial for technical leaders and decision makers to understand their organization's data architecture and how each platform component serves business needs. A basic understanding of data & analytics architectures and systems is desirable along with beginner's level understanding of AWS Cloud.Table of ContentsModern Data Architecture on AWSScalable Data LakesBatch Data IngestionStreaming Data IngestionData ProcessingInteractive AnalyticsData WarehousingData SharingData FederationPredictive AnalyticsGenerative AIOperational AnalyticsBusiness IntelligenceData GovernanceData MeshPerformant and Cost-effective Data PlatformAutomate, Operationalize and Monetize
Make data-driven, informed decisions and enhance your statistical expertise in Python by turning raw data into meaningful insightsPurchase of the print or Kindle book includes a free PDF eBookKey Features:Gain expertise in identifying and modeling patterns that generate successExplore the concepts with Python using important libraries such as stats modelsLearn how to build models on real-world data sets and find solutions to practical challengesBook Description:The ability to proficiently perform statistical modeling is a fundamental skill for data scientists and essential for businesses reliant on data insights. Building Statistical Models with Python is a comprehensive guide that will empower you to leverage mathematical and statistical principles in data assessment, understanding, and inference generation.This book not only equips you with skills to navigate the complexities of statistical modeling, but also provides practical guidance for immediate implementation through illustrative examples. Through emphasis on application and code examples, you'll understand the concepts while gaining hands-on experience. With the help of Python and its essential libraries, you'll explore key statistical models, including hypothesis testing, regression, time series analysis, classification, and more.By the end of this book, you'll gain fluency in statistical modeling while harnessing the full potential of Python's rich ecosystem for data analysis.What You Will Learn:Explore the use of statistics to make decisions under uncertaintyAnswer questions about data using hypothesis testsUnderstand the difference between regression and classification modelsBuild models with stats models in PythonAnalyze time series data and provide forecastsDiscover Survival Analysis and the problems it can solveWho this book is for:If you are looking to get started with building statistical models for your data sets, this book is for you! Building Statistical Models in Python bridges the gap between statistical theory and practical application of Python. Since you'll take a comprehensive journey through theory and application, no previous knowledge of statistics is required, but some experience with Python will be useful.
Enhance your career as an Azure architect with cutting-edge tools, expert guidance, and resources from industry leadersKey Features:Develop your business case for the cloud with technical guidance from industry expertsAddress critical business challenges effectively by leveraging proven combinations of Azure servicesTackle real-world scenarios by applying practical knowledge of reference architecturesPurchase of the print or Kindle book includes a free PDF eBookBook Description:Azure is a sophisticated technology that requires a detailed understanding to reap its full potential and employ its advanced features. This book provides you with a clear path to designing optimal cloud-based solutions in Azure, by delving into the platform's intricacies.You'll begin by understanding the effective and efficient security management and operation techniques in Azure to implement the appropriate configurations in Microsoft Entra ID. Next, you'll explore how to modernize your applications for the cloud, examining the different computation and storage options, as well as using Azure data solutions to help migrate and monitor workloads. You'll also find out how to build your solutions, including containers, networking components, security principles, governance, and advanced observability. With practical examples and step-by-step instructions, you'll be empowered to work on infrastructure-as-code to effectively deploy and manage resources in your environment.By the end of this book, you'll be well-equipped to navigate the world of cloud computing confidently.What You Will Learn:Implement and monitor cloud ecosystem including, computing, storage, networking, and securityRecommend optimal services for performance and scaleProvide, monitor, and adjust capacity for optimal resultsCraft custom Azure solution architecturesDesign computation, networking, storage, and security aspects in AzureImplement and maintain Azure resources effectivelyWho this book is for:This book is an indispensable resource for Azure architects looking to develop cloud-based services along with deploying and managing applications within the Microsoft Azure ecosystem. It caters to professionals responsible for crucial IT operations, encompassing budgeting, business continuity, governance, identity management, networking, security, and automation. If you have prior experience in operating systems, virtualization, infrastructure, storage structures, or networking, and aspire to master the implementation of best practices in the Azure cloud, then this book will become your go-to guide.
Begin your exploration into cloud computing by developing deep knowledge of cloud technologies, enhancing hands-on skills, and achieving proficiency in cloudKey FeaturesTeach yourself all about cloud computing with this easy-to-follow guideDevelop a well-rounded skillset-from fundamentals to data, machine learning, and securityWork on real life industrial projects, business use cases, and personal cloud career developmentPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThis book is an all-inclusive guide for IT professionals to master cloud computing concepts by building a broad and deep cloud knowledge base, developing hands-on cloud skills, and achieving professional cloud certifications. If you're a beginner with basic computer hardware and software understanding, this book provides the means to transitions into a cloud computing career.Starting with a focus on the Amazon cloud, you'll be introduced to fundamental AWS cloud services, followed by advanced AWS cloud services in the domains of data, machine learning, and security. Next, you'll build proficiency in Microsoft Azure cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds, differentiating their unique features, along with leveraging real-life cloud project implementations on these cloud platforms. Finally, you'll get guidance on cloud certifications and career development.Walking through this cloud computing book, you'll systematically establish a robust footing in AWS, Azure, and GCP, and emerge as a cloud-savvy professional, equipped with cloud certificates to validate your skills.What you will learnDevelop the core skills needed to work with cloud computing platforms such as AWS, Azure, and GCPGain proficiency in compute, storage, and networking services across multi-cloud and hybrid-cloud environmentsIntegrate cloud databases, big data, and machine learning services in multi-cloud environmentsDesign and develop data pipelines, encompassing data ingestion, storage, processing, and visualization in the cloudsImplement machine learning pipelines in multi-cloud environmentSecure cloud infrastructure ecosystems with advanced cloud security servicesWho this book is forWhether you're a beginner in cloud computing or an experienced professional seeking to expand your skills, this meticulously designed study book is for anyone in the information technology domain aiming to thrive in the realm of cloud computing. With this comprehensive roadmap, you'll have the tools to build a successful cloud computing career.Table of ContentsAmazon EC2 and Cloud Compute ServicesAmazon Cloud Storage ServicesAmazon Cloud Networking ServicesAmazon Cloud Database ServicesAmazon Cloud Big Data ServicesAmazon Cloud Machine Learning ServicesAmazon Cloud Security ServicesGoogle Cloud Foundation ServicesGoogle Cloud Data ServicesGoogle Cloud AI ServicesGoogle Cloud Security ServicesAzure Cloud Foundation ServicesAzure Cloud Data ServicesAzure Cloud AI ServicesAzure Cloud Security ServicesAchieving Cloud CertificationsBuilding a Successful Cloud Computing Career
Explore the beacon chain, Ethereum's PoS consensus, and the upcoming merge of Eth1 and Eth2, along with the challenges of scaling Ethereum, and an overview of L1 and L2 scaling solutionsPurchase of the print or Kindle book includes a free PDF eBookKey Features:Learn new development with Ethereum 2.0 and the planned merge of Eth1 and Eth2Build, develop, and test end-to-end Ethereum dApps using Solidity, Node.js, and Web3Setup private blockchains with Ethereum and delve into its wallets systemBook Description:Ethereum is a blockchain-based, decentralized computing platform that allows you to run smart contracts. With this book, you'll discover the latest Ethereum tools, frameworks, wallets, and layer 2, along with setting up and running decentralized applications for the complete, end-to-end development experience.Learn Ethereum, 2nd Edition is a comprehensive overview of the Ethereum ecosystem, exploring its concepts, mechanisms, and decentralized application development process. You'll delve into Ethereum's internals, technologies, and tools, including Ethereum 2.0 and the Ethereum Virtual Machine (EVM), gas, and its account systems. You'll also explore Ethereum's transition to proof of stake, L1/L2 scaling solutions, DeFi protocols, and the current marketplace. Additionally, you'll learn about EVM-compatible blockchains, connectivity techniques, and advanced topics such as sharding, off-chain scaling, DAOs, Metaverse, and NFTs.By the end of this book, you'll be well-equipped to write smart contracts and develop, test, and deploy DApps using various tools, wallets, and frameworks.What You Will Learn:Understand blockchain, cryptocurrency, and architecturesExplore decentralized finance protocolsGrasp how EVM-compatible blockchain networks workDiscover the latest developments in EthereumUse Solidity and Web3 API fundamentals on blockchain frameworksDevelop your own personalized cryptocurrencyBuild tailor-made smart contracts and NFT marketplace DAppsSet up an Ethereum private chainWho this book is for:This book is for blockchain developers and architects looking to learn the Ethereum blockchain fundamentals and those who want to build real-world decentralized applications using Solidity. Basic knowledge of an object-oriented programming language such as JavaScript will be useful but not mandatory.
Move legacy applications to a hyper-scale cloud such as Azure using best practices and surefire techniquesKey Features:Meet the needs of mainframe applications using hyper-scale platformMove from a monolithic architecture to a modern cloud architecture by employing a perspective planAvoid the big bang approach to modernization when in need of a phased approachPurchase of the print or Kindle book includes a free PDF eBookBook Description:Organizations have varying circumstances, objectives, and prerequisites when contemplating a hyper-scale cloud solution transformation to a platform such as Azure. Modernizing Legacy Applications to Microsoft Azure uncovers potential scenarios and provides choices, methodologies, techniques, and prospective possibilities for transitioning from legacy applications to the Microsoft Azure environment.You'll start by understanding the legacy systems and the main concerns regarding migration. Then, you'll investigate why distributed architectures are compelling and the various components of the Azure platform needed during migration. After that, you'll explore the approaches to modernizing legacy applications and the Rs of modernizing (i.e., rehost, refactor, rearchitect, and retire). You'll also learn about integration approaches and potential pitfalls.By the end of this book, you'll be well equipped to modernize your legacy workloads while being aware of pitfalls and best practices.What You Will Learn:Understand your current legacy estate's options before moving to AzureMove to a cloud environment from your legacy applicationsBuild equivalent or superior application SLAs in AzureUse interoperability to enable a phased approachIntegrate DevOps to help accelerate modernizationExtend application functionality after migrationWho this book is for:This book is for both decision makers and implementers including CIOs, CTOs, data and application architects, developers (both legacy and cloud), and business strategists. Prior knowledge of legacy languages and modern cloud-based languages like C#/.NET and Java would be helpful.
Develop Python applications using an enterprise-based approach with unit and acceptance tests by following agile methods to create a minimum viable product (MVP) and iteratively add featuresKey Features:Master Python and related technologies by working on 12 hands-on projectsAccelerate your career by building a personal project portfolioExplore data acquisition, preparation, and analysis applicationsPurchase of the print or Kindle book includes a free PDF eBookBook Description:In today's competitive job market, a project portfolio often outshines a traditional resume. Python Real-World Projects empowers you to get to grips with crucial Python concepts while building complete modules and applications. With two dozen meticulously designed projects to explore, this book will help you showcase your Python mastery and refine your skills.Tailored for beginners with a foundational understanding of class definitions, module creation, and Python's inherent data structures, this book is your gateway to programming excellence. You'll learn how to harness the potential of the standard library and key external projects like JupyterLab, Pydantic, pytest, and requests. You'll also gain experience with enterprise-oriented methodologies, including unit and acceptance testing, and an agile development approach. Additionally, you'll dive into the software development lifecycle, starting with a minimum viable product and seamlessly expanding it to add innovative features.By the end of this book, you'll be armed with a myriad of practical Python projects and all set to accelerate your career as a Python programmer.What You Will Learn:Explore core deliverables for an application including documentation and test casesDiscover approaches to data acquisition such as file processing, RESTful APIs, and SQL queriesCreate a data inspection notebook to establish properties of source dataWrite applications to validate, clean, convert, and normalize source dataUse foundational graphical analysis techniques to visualize dataBuild basic univariate and multivariate statistical analysis toolsCreate reports from raw data using JupyterLab publication toolsWho this book is for:This book is for beginner-to-intermediate level Python programmers looking to enhance their resume by adding a portfolio of 12 practical projects. A basic understanding of the Python language and its aligned technologies is a must. The book helps you polish your Python skills and project-building prowess without delving into basic Python fundamentals.
Elevate your technical career with practical guidance, best practices, and actionable insights shared by industry expertsKey FeaturesDevelop the right skills to advance your career with comprehensive skill developmentExplore practical examples and case studies for real-world career guidanceUnderstand the importance of networking and community engagement for professional growthPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionWritten by industry experts that have spent the last 20+ years helping developers grow their careers, this book offers invaluable insights and guidance tailored to the specific needs of technical professionals. By discovering the secret of continuous learning and adapting in the ever-evolving field of software development, you'll explore various learning paths with formal and informal methods, as well as gain an understanding of the value of certifications to validate your skills. This book will teach you the significance of building a strong support network, holding crucial conversations, and taking ownership of your career growth. You'll delve into acquiring both soft and hard skills, becoming a well-rounded and sought-after developer. Packed with practical examples, stories of successful developers, and real-world applications, the chapters will equip you with actionable advice on how to push beyond your comfort zone and embracing communities to enhance your teamwork abilities. Additionally, you'll uncover the benefits of joining open-source projects, speaking at conferences, and building a personal brand to amplify your visibility and reputation. By the end of this book, you'll have a well-laid-out long-term and short-term plan for your career progression, equipping you with advanced technical skills, strategic thinking, and the ability to effectively manage relationships within your organization.What you will learnExplore skills needed to grow your careerParticipate in community and mentorship programsBuild your technical knowledge for growthDiscover how to network and use social mediaUnderstand the impact of public speakingIdentify the critical conversations to advance your careerParticipate in non-technical activities to enhance your careerWho this book is forThis book is for technical professionals, particularly developers, seeking practical career growth guidelines and best practices. It addresses both junior and senior developers, offering valuable insights and experiences from within the developer community.Table of ContentsThe secret to learn technology fast and continuouslyChoose your best path for Learning, Training and CertificationsOptimize Your Support Network for GrowthAcquire the right Soft and Hard skills deliberatelyPush yourself by improving outside of your comfort zoneBecome a team player by embracing communitiesFocus your growth by giving and receiving mentoringBe part of a larger group: Meeting people at User Groups and MeetupsGrow your network using Social MediaBuild deep, lasting relationships at Conferences and in person activitiesBuild trust with top developers and solve important problems by joining Open SourceBuild trust at scale by sharing Publicly through Speaking and blogsBe a leader, Manage up, down and across your organizationStep up your technology game: Define technology instead of merely using itBuild your Personal brand and be respected and requested as a trusted advisor
A step-by-step guide to building cost-effective and complete home automation DIY projects using tools such as Home Assistant, Raspberry Pi, IoT devices, the Tasmota sensor, ESP32, and GrafanaKey Features:- Learn by doing using real-life practical examples to build your own home automation system- Create, hack, and configure IoT devices through hands-on projects to be used with or without Home Assistant- Customize your home automation system using Home Assistant, Node-RED, InfluxDB, and Grafana- Purchase of the print or Kindle book includes a free PDF eBookBook Description:Picture a home where you can adjust the lighting based on the time of day or when movement is detected. In this same home, you can also detect when a door is unexpectedly opened or an alarm is triggered in response to any suspicious activity. Such automated devices form part of a smart home, and the exciting part is that this book teaches you how to create and manage these devices all by yourself.This book helps you create your own ecosystem to automate your home using Home Assistant software. You'll begin by understanding the components of a home automation system and learn how to create, hack, and configure them to operate seamlessly. Then, you'll set up Home Assistant on a Raspberry Pi to work as a home automation server, build your own IoT sensors based on ESP32/ESP8266, and set up real-life automation use cases using hands-on examples and projects. The chapters will also guide you in using software tools such as Node-RED, InfluxDB, and Grafana to manage, present, and use data collected from your Home Automation devices. Finally, you'll gain insights into new technologies and trends in the home automation space to help you continue with your learning journey.By the end of this book, you'll be able to build your own creative, IoT-based home automation system using different hardware and software technologies.What You Will Learn:- Understand the fundamental concepts of home automation systems- Set up a home automation system using Home Assistant and Raspberry Pi- Create and configure ESP8266-based sensors to work with Home Assistant- Hack a commercial actuator to work with Home Assistant using Tasmota- Create automations, customize, and use applications with Home Assistant- Leverage IoT software tools to take your home automation to the next level- Work on hands-on projects, including LED strip lights and an ESP32 five-zone temperature logger- Explore home automation FAQs, emerging technologies, and trendsWho this book is for:The book is for engineers, developers, students, makers, and enthusiasts who're working on or interested in working with electronics and IoT devices, embedded systems, systems integration, computer software, and coding to develop their own smart home automation systems. Technicians, teachers, and other professionals who want to learn home automation-related technologies will also find this book useful. Prior experience of working with Raspberry Pi, creating hardware prototypes, and software programming will be beneficial.Table of Contents- Understanding Home Automation Systems- Getting Started with Home Assistant- Hands-On Project 1 - Creating Your Own Sensor- Hacking a Commercial Actuator to Work with Home Assistant- Creating Automations Using Home Assistant- Doing More Using Integrations and Customizations- Extending Home Automation Capabilities Using Add-ons- Installing and Setting Up Home Assistant Container- Hands-On Project 2 - Creating an LED Strip Controller and Adding It to Home Assistant(N.B. Please use the Read Sample option to see further chapters)
Transform your machine learning projects into successful deployments with this practical guide on how to build and scale solutions that solve real-world problemsIncludes a new chapter on generative AI and large language models (LLMs) and building a pipeline that leverages LLMs using LangChainKey FeaturesThis second edition delves deeper into key machine learning topics, CI/CD, and system designExplore core MLOps practices, such as model management and performance monitoringBuild end-to-end examples of deployable ML microservices and pipelines using AWS and open-source toolsBook DescriptionThe Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field.The book takes an examples-based approach to help you develop your skills and covers the technical concepts, implementation patterns, and development methodologies you need. You'll explore the key steps of the ML development lifecycle and create your own standardized "model factory" for training and retraining of models. You'll learn to employ concepts like CI/CD and how to detect different types of drift.Get hands-on with the latest in deployment architectures and discover methods for scaling up your solutions. This edition goes deeper in all aspects of ML engineering and MLOps, with emphasis on the latest open-source and cloud-based technologies. This includes a completely revamped approach to advanced pipelining and orchestration techniques.With a new chapter on deep learning, generative AI, and LLMOps, you will learn to use tools like LangChain, PyTorch, and Hugging Face to leverage LLMs for supercharged analysis. You will explore AI assistants like GitHub Copilot to become more productive, then dive deep into the engineering considerations of working with deep learning.What you will learnPlan and manage end-to-end ML development projectsExplore deep learning, LLMs, and LLMOps to leverage generative AIUse Python to package your ML tools and scale up your solutionsGet to grips with Apache Spark, Kubernetes, and RayBuild and run ML pipelines with Apache Airflow, ZenML, and KubeflowDetect drift and build retraining mechanisms into your solutionsImprove error handling with control flows and vulnerability scanningHost and build ML microservices and batch processes running on AWSWho this book is forThis book is designed for MLOps and ML engineers, data scientists, and software developers who want to build robust solutions that use machine learning to solve real-world problems. If you're not a developer but want to manage or understand the product lifecycle of these systems, you'll also find this book useful. It assumes a basic knowledge of machine learning concepts and intermediate programming experience in Python. With its focus on practical skills and real-world examples, this book is an essential resource for anyone looking to advance their machine learning engineering career.Table of ContentsIntroduction to ML EngineeringThe Machine Learning Development ProcessFrom Model to Model Factory Packaging UpDeployment Patterns and ToolsScaling UpDeep Learning, Generative AI, and LLMOps Building an Example ML MicroserviceBuilding an Extract, Transform, Machine Learning Use Case
Find all the information, exercises, and tools to ace the Splunk Enterprise Certified Admin exam in one place Key Features:Explore various administration topics including installation, configuration, and user managementGain a deep understanding of data inputs, parsing, and field extractionExcel in the Splunk Enterprise Admin exam with the help of self-assessment questions and mock examsPurchase of the print or Kindle book includes a free PDF eBookBook Description:The IT sector's appetite for Splunk and skilled Splunk developers continues to surge, offering more opportunities for developers with each passing decade. If you want to enhance your career as a Splunk Enterprise administrator, then Splunk 9.x Enterprise Certified Admin Guide will not only aid you in excelling on your exam but also pave the way for a successful career.You'll begin with an overview of Splunk Enterprise, including installation, license management, user management, and forwarder management. Additionally, you'll delve into indexes management, including the creation and management of indexes used to store data in Splunk. You'll also uncover config files, which are used to configure various settings and components in Splunk.As you advance, you'll explore data administration, including data inputs, which are used to collect data from various sources, such as log files, network protocols (TCP/UDP), APIs, and agentless inputs (HEC).You'll also discover search-time and index-time field extraction, used to create reports and visualizations, and help make the data in Splunk more searchable and accessible. The self-assessment questions and answers at the end of each chapter will help you gauge your understanding.By the end of this book, you'll be well versed in all the topics required to pass the Splunk Enterprise Admin exam and use Splunk features effectively.What You Will Learn:Explore Splunk Enterprise 9.x features and usageInstall, configure, and manage licenses and users for SplunkCreate and manage indexes for data storageExplore Splunk configuration files, their precedence, and troubleshootingManage forwarders and source data into Splunk from various resourcesParse and transform data to make it easy to useExtract fields from data at search and index time for data analysisEngage with mock exam questions to simulate the Splunk admin examWho this book is for:This book is for data professionals looking to gain certified Splunk administrator credentials. It will also help data analysts, Splunk users, IT experts, security analysts, and system administrators seeking to explore the Splunk admin realm, understand its functionalities, and become proficient in effectively administering Splunk Enterprise. This guide serves as both a valuable resource for learning and a practical manual for administering Splunk Enterprise, encompassing features beyond the scope of certification preparation.
Create and deploy production-grade microservices-based applications with this latest edition updated to Spring Boot 3, Java 17, and Spring Cloud 2022Purchase of the print or Kindle book includes a free PDF eBookKey Features:Build cloud-native production-ready microservices and stay ahead of the curveUnderstand the challenges of building large-scale microservice architecturesLearn how to get the best out of the latest updates, including Spring Boot 3, Spring Cloud, Kubernetes, and IstioBook Description:Looking to build and deploy microservices but not sure where to start? Check out Microservices with Spring Boot 3 and Spring Cloud, Third Edition.With a practical approach, you'll begin with simple microservices and progress to complex distributed applications. Learn essential functionality and deploy microservices using Kubernetes and Istio.This book covers Java 17, Spring Boot 3, and Spring Cloud 2022. Java EE packages are replaced with the latest Jakarta EE packages. Code examples are updated and deprecated APIs have been replaced, providing the most up to date information. Gain knowledge of Spring's AOT module, observability, distributed tracing, and Helm 3 for Kubernetes packaging.Start with Docker Compose to run microservices with databases and messaging services. Progress to deploying microservices on Kubernetes with Istio. Explore persistence, resilience, reactive microservices, and API documentation with OpenAPI. Learn service discovery with Netflix Eureka, edge servers with Spring Cloud Gateway, and monitoring with Prometheus, Grafana, and the EFK stack.By the end, you'll build scalable microservices using Spring Boot and Spring Cloud.What You Will Learn:Build reactive microservices using Spring BootDevelop resilient and scalable microservices using Spring CloudUse OAuth 2.1/OIDC and Spring Security to protect public APIsImplement Docker to bridge the gap between development, testing, and productionDeploy and manage microservices with KubernetesApply Istio for improved security, observability, and traffic managementWrite and run automated microservice tests with JUnit, test containers, Gradle, and bashUse Spring AOT and GraalVM to native compile the microservicesUse Micrometer Tracing for distributed tracingWho this book is for:If you're a Java or Spring Boot developer learning how to build microservice landscapes from scratch, then this book is for you. To get started, you need some prior experience in building apps with Java or Spring Boot.
Et al. is a satirical academic journal that uses machine learning and scientific principles on absurd studies, from the cat Lord Whiskers' role in the extinction of the dodo bird to the quantum mysteries of untidy toddler rooms.Key FeaturesConducts satirical research on topics ranging from quantum computing to clingy robot dog algorithmsAnswers questions like "Can a computer understand a Scotsman?" and "Is Sarah Palin real?"Secures the power grid and your home from the prying eyes of government drones a.k.a. birdsExpands science by studying cow-based atmospheres, and the flavortown center of the brainSolves climate change and saves the world by proposing a banana-based fission reactorNullifies the possibility of getting lost at the fair with a mirror-house escape algorithmBook DescriptionTired of the same old math, science, statistics, and programming memes people post online and want something a little more elaborate? This is the book for you.Tremble as we make up all our own facts and data, hand-draw diagrams in MS Paint, and quote from fictional studies and journals. Cower as authors write in the first person because their study is just a little too personal for them. Recoil from the sheer mass of oversimplified methodology, distilling someone's entire thesis into a paragraph of jokes crude enough to make it into a Mike Myers movie.Over the last few years, we have taken arguments that you would normally have after four Jack and cokes at game night and turned them into properly formatted research papers with a writing tone serious enough to confuse the uninitiated. These papers are high-effort jokes by researchers and scientists for researchers and scientists. They cover a range of topics such as the consequences of re-releasing tourists back into Yellowstone National Park after COVID-19, how to play StarCraft competitively online on a quantum computer, and most importantly, how trees around the globe are becoming increasingly radicalized.What you will learnHow to draw a graph using MS Paint, maybeWhether Sarah Palin is a figment of your imaginationHow one pirate cat brought about the extinction of the beloved dodoWhy rabbits used to be jerks back in the dayIf you actually learn anything from these articles, get your memory erased immediatelyWho this book is forThis book is for researchers and those who love science mingled with humor. It's for those who are a little too tired of the talking heads and futurists of the science world and would like something more entertaining in the form of absurd speculative studies by researchers as unbelievable as their work. Anyone who has experienced academic writing, or the tribulations of any research institution will enjoy the wide range of bizarre, yet real-world topics compiled in this book. Even if you don't know much about the subject, we usually have a background section.Table of ContentsThe Pirate Kitty Theory: How a House Cat BeingCows All the Way Down: Could Cow-Based Planetoids Support Methane Atmospheres?Ecological Impacts of Re-Releasing Tourists into YellowstoneThe Great Rabbit War of 863AD: Myth or Historical Fact?The Cat Homing Infrared Laser Drone Defense (CHILD) System: A Novel Approach to Suburban DefenseThe Sarah Palin Mandela Effect: How America Believes in a Fictional PoliticianUtilitarianism, Shame, and Mysticism: Autonomous Vehicle Moral Compass Design and AnalysisA Comparative Analysis of Trevor's Mom: Age Estimation MethodologyAdaptive Smart Grids for Migratory Government Drones(N.B. Please use the Look Inside option to see further chapters)
Explore how to provision, manage, and scale your infrastructure using Infrastructure as Code (IaC) with TerraformPurchase of the print or Kindle book includes a free PDF eBookKey Features:Get up and running with the latest version of Terraform (v1+) CLIDiscover how to deploy Kubernetes resources with TerraformLearn how to troubleshoot common Terraform issuesBook Description:HashiCorp Configuration Language (HCL) has changed how we define and provision data center infrastructure with the launch of Terraform - a top-tier product for building Infrastructure as Code (IaC). Terraform Cookbook shows you how to leverage Terraform to manage complex cloud infrastructure with ease.This new edition has been updated to include real-world examples for provisioning Cloud infrastructure(mainly for Azure, but also a dedicated chapter for AWS and GCP) with Terraform. You'll delve into manual and automated testing with Terraform configurations, creating and managing a balanced, efficient, reusable infrastructure with Terraform modules. You'll learn how to automate the deployment of Terraform configuration with continuous integration and continuous delivery (CI/CD). Besides, several new chapters have been added that describe the use of Terraform for Docker and Kubernetes, and explain how to test Terraform configurations using different tools to check code and security compliance. A complete chapter is dedicated to mastering Terraform Cloud and the latest chapter covers troubleshooting common Terraform issues and provides solutions for frequently encountered errors.By the end of this book, you'll have developed the skills needed to get the most value out of Terraform and to effectively manage your infrastructure.What You Will Learn:WriteTerraform configuration to provision cloud and Kubernetes infrastructure using IaC best practicesUse the Terraform command line adapted to appropriate use casesAutomate the deployment of Terraform configurationDiscover manipulation of the Terraform StateUncover IaC for developers with the CDKTF Cloud Development Kit for TerraformAdd and apply test rules and compliance security in Terraform configurationUse Terraform Cloud to improve Team collaboration around Terraform provisioningExplore debugging and troubleshooting common Terraform errorsWho this book is for:This book is for developers, operators, and DevOps engineers looking to improve their workflow and use Infrastructure as Code. Experience with Microsoft Azure, Jenkins, shell scripting, and DevOps practices is required to get the most out of this Terraform book.
Strategize and create automated business workflows with Zapier, including AI-integrated functionalities such as the ChatGPT plugin and the OpenAI integration, to minimize repetitive tasks without using codeKey Features:Discover the newest Zapier features including OpenAI integration and the ChatGPT pluginExplore expert tips and real-life examples to connect 6000+ business apps and automate tasks with ZapierLearn how to manage your account effectively and troubleshoot problems with your ZapsPurchase of the print or Kindle book includes a free PDF eBookBook Description:Organizations experience significant issues with productivity when dealing with manual and repetitive tasks. Automate it with Zapier and Generative AI, second edition has been extensively revised to help you analyze your processes and identify repetitive tasks that can be automated between 6000+ cloud-based business applications.This book includes all Zapier's newest features such as AI functionality using the ChatGPT plugin, drafts, reordering and duplicating steps and paths, subfolders and version history, as well as built-in apps such as Looping, Sub-Zap, Interfaces, Tables, and Transfer. The chapters also contain examples covering various use cases sourced from the Zapier user community.You'll learn how to implement automation in your organization along with key principles and terminology, and take the first steps toward using Zapier. As you advance, you'll learn how to use Zapier's native functionality and all 27 built-in apps such as Filter, Paths, Formatter, Digest, and Scheduler to enable you to build multi-step Zaps. You'll also discover how to manage your Zapier account effectively, as well as how to troubleshoot technical problems with your workflows, and use the OpenAI integration to automate AI tasks.By the end of this book, you'll be able to automate your manual and repetitive tasks using Zapier.What You Will Learn:Think outside the box to simplify business workflows and solve productivity problemsStrategize how to optimally structure and build your workflow automation in Zapier to prevent errors and excessive task usageExplore the latest built-in apps including Transfer, Interfaces, Tables, Looping, Sub-Zap, and the ChatGPT pluginDiscover how to use AI-integrated apps and features with automationCreate complex multi-step Zaps using logic, formatting, and calculationsEffectively manage your account and troubleshoot problems with your ZapsWho this book is for:This book is for business owners, operations managers, teams in micro, small, or medium-sized businesses looking at automating repetitive tasks & increasing their productivity using Zapier and AI-integrated features. Service providers offering digital process improvement, systemization, and automation services to their clients such as solutions architects, process consultants, business analysts, virtual assistants, CRM consultants, OBMs, bookkeepers & accountants will find this book extremely useful. Suitable for new and experienced Zapier users.
Supercharge and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scaleKey Features:Leverage supervised learning to build binary classification, multi-class classification, and regression modelsLearn to use unsupervised learning using the K-means clustering methodMaster the art of time series forecasting using Redshift MLPurchase of the print or Kindle book includes a free PDF eBookBook Description:Amazon Redshift Serverless enables organizations to run petabyte-scale cloud data warehouses quickly and in a cost-effective way, enabling data science professionals to efficiently deploy cloud data warehouses and leverage easy-to-use tools to train models and run predictions. This practical guide will help developers and data professionals working with Amazon Redshift data warehouses to put their SQL knowledge to work for training and deploying machine learning models.The book begins by helping you to explore the inner workings of Redshift Serverless as well as the foundations of data analytics and types of data machine learning. With the help of step-by-step explanations of essential concepts and practical examples, you'll then learn to build your own classification and regression models. As you advance, you'll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, you'll discover best practices for implementing serverless architecture with Redshift.By the end of this book, you'll be able to configure and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale.What You Will Learn:Utilize Redshift Serverless for data ingestion, data analysis, and machine learningCreate supervised and unsupervised models and learn how to supply your own custom parametersDiscover how to use time series forecasting in your data warehouseCreate a SageMaker endpoint and use that to build a Redshift ML model for remote inferenceFind out how to operationalize machine learning in your data warehouseUse model explainability and calculate probabilities with Amazon Redshift MLWho this book is for:Data scientists and machine learning developers working with Amazon Redshift who want to explore its machine-learning capabilities will find this definitive guide helpful. A basic understanding of machine learning techniques and working knowledge of Amazon Redshift is needed to make the most of this book.
Master the art of mathematical modeling through practical examples, use cases, and machine learning techniquesKey Features:Gain a profound understanding of various mathematical models that can be integrated with machine learningLearn how to implement optimization algorithms to tune machine learning modelsBuild optimal solutions for practical use casesPurchase of the print or Kindle book includes a free PDF eBookBook Description:Mathematical modeling is the art of transforming a business problem into a well-defined mathematical formulation. Its emphasis on interpretability is particularly crucial when deploying a model to support high-stake decisions in sensitive sectors like pharmaceuticals and healthcare.Through this book, you'll gain a firm grasp of the foundational mathematics underpinning various machine learning algorithms. Equipped with this knowledge, you can modify algorithms to suit your business problem. Starting with the basic theory and concepts of mathematical modeling, you'll explore an array of mathematical tools that will empower you to extract insights and understand the data better, which in turn will aid in making optimal, data-driven decisions. The book allows you to explore mathematical optimization and its wide range of applications, and concludes by highlighting the synergetic value derived from blending mathematical models with machine learning.Ultimately, you'll be able to apply everything you've learned to choose the most fitting methodologies for the business problems you encounter.What You Will Learn:Understand core concepts of mathematical models and their relevance in solving problemsExplore various approaches to modeling and learning using PythonWork with tested mathematical tools to gather meaningful insightsBlend mathematical modeling with machine learning to find optimal solutions to business problemsOptimize ML models built with business data, apply them to understand their impact on the business, and address critical questionsApply mathematical optimization for data-scarce problems where the objective and constraints are knownWho this book is for:If you are a budding data scientist seeking to augment your journey with mathematics, this book is for you. Researchers and R&D scientists will also be able to harness the concepts covered to their full potential. To make the best use of this book, a background in linear algebra, differential equations, basics of statistics, data types, data structures, and numerical algorithms will be useful.
Build, design, and improve advanced business intelligence solutions using Tableau's newest updates, including new Tableau Desktop, Tableau Prep, and Tableau Server featuresPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesMaster new Tableau 2023 features to solve real-world analytics challengesLearn how to use both pre-defined and your own Machine Learning models in TableauHow to manage Data Governance and secure high data qualityBook DescriptionThis edition of the bestselling Tableau guide will teach you how to leverage Tableau's newest features and offerings in various paradigms of the BI domain. Updated with fresh topics, including the newest features in Tableau Server,Prep, and Desktop, as well as up-to-date examples, this book will take you from mastering essential Tableau concepts to advance functionalities. A chapter on data governance has also been added.Throughout this book, you'll learn how to use Tableau Hyper files and Prep Builder to easily perform data preparation and handling, as well as complex joins, spatial joins, unions, and data blending tasks using practical examples. You'll also get to grips with executing data densification and explore other expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions.Later chapters will teach you all about improving dashboard performance, connecting to Tableau Server, and understanding data visualization with examples. Finally, you'll cover advanced use cases, such as self-service analysis, time series analysis, geo-spatial analysis, and how to connect Tableau to Python and R to implement programming functionalities within Tableau.By the end of this book, you'll have mastered Tableau 2023 and be able to tackle common and advanced challenges in the BI domain.What you will learnLearn about various Tableau components, such as calculated fields, table calculations, and LOD expressionsMaster ETL (Extract, Transform, Load) techniques using Tableau Prep BuilderExplore and implement data storytelling with Python and RUnderstand Tableau Exchange by using accelerators, extensions, and connectorsInteract with Tableau Server to understand its functionalitiesStudy advanced visualizations and dashboard creation techniquesBrush up on powerful self-service analytics, time series analytics, and geo-spatial analyticsFind out why data governance matters and how to implement itWho this book is forThis book is designed for business analysts, business intelligence professionals, and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. Prior exposure to Tableau will help you get to grips with the features more quickly, but it's not a prerequisite.Table of ContentsReviewing the BasicsGetting Your Data ReadyUsing Tableau Prep BuilderLearning about Joins, Blends, and Data StructuresIntroducing Table CalculationsUtilizing OData, Data Densification, Big Data, and Google BigQueryPracticing Level of Detail CalculationsGoing Beyond the BasicsWorking with MapsPresenting with TableauDesigning Dashboards and Best Practices for VisualizationsLeveraging Advanced AnalyticsImproving PerformanceExploring Tableau Server and Tableau CloudIntegrating Programming LanguagesDeveloping Data Governance Practices
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