Mastering Swift

Jon Hoffman

ASP.NET Core 8 and Angular. Full-stack web development with ASP.NET Core 8 and Angular - Sixth Edition

Valerio De Sanctis

If you want to learn how to use ASP.NET Core with Angular effectively, this hands-on guide is for you.Improve the way you create, debug, and deploy web applications while keeping up to date with the latest developments in .NET 8 and modern Angular, including .NET Minimal APIs and the new Angular standalone API defaults.You’ll begin by setting up SQL Server 2022 and building a data model with Entity Framework Core. You’ll progress to fetching and displaying data, handling user input with Angular reactive forms, and implementing front-end and back-end validators for maximum effect. After that, you will perform advanced debugging and explore unit testing features with xUnit for .NET, and Jasmine and Karma for Angular. You’ll use Identity API endpoints in ASP.NET Core and functional route guards in Angular to add authentication and authorization to your apps. Finally, you’ll learn how to deploy to Windows, Linux, and Azure.By the end of this book, you will understand how to tie together the front-end and back-end to build and deploy secure and robust web applications.

Terraform Cookbook. Efficiently define, launch, and manage Infrastructure as Code across various cloud platforms

Mikael Krief, Mitchell Hashimoto

HashiCorp Configuration Language (HCL) has changed how we define and provision a data center infrastructure with the launch of Terraform—one of the most popular and powerful products for building Infrastructure as Code. This practical guide will show you how to leverage HashiCorp's Terraform tool to manage a complex infrastructure with ease.Starting with recipes for setting up the environment, this book will gradually guide you in configuring, provisioning, collaborating, and building a multi-environment architecture. Unlike other books, you’ll also be able to explore recipes with real-world examples to provision your Azure infrastructure with Terraform. Once you’ve covered topics such as Azure Template, Azure CLI, Terraform configuration, and Terragrunt, you’ll delve into manual and automated testing with Terraform configurations. The next set of chapters will show you how to manage a balanced and efficient infrastructure and create reusable infrastructure with Terraform modules. Finally, you’ll explore the latest DevOps trends such as continuous integration and continuous delivery (CI/CD) and zero-downtime deployments.By the end of this book, you’ll have developed the skills you need to get the most value out of Terraform and manage your infrastructure effectively.

Extending Dynamics 365 Finance and Operations Apps with Power Platform. Integrate Power Platform solutions to maximize the efficiency of your Finance & Operations projects

Adria Ariste Santacreu

Uncover the synergy between Microsoft Power Platform and its integration with Dynamics 365 Finance & Operations (F&O) with this essential guide to implementing low-code and no-code concepts to not only extend and enhance F&O but also improve maintainability and speed up development.Systematically exploring Power Platform, this book covers topics such as Dataverse, Power Automate, Power Apps, and Power BI using real-world scenarios in Dynamics 365 F&O to offer practical insights. You’ll then master the integration of F&O and Power Platform using dual-write and virtual tables, and delve into process automation with Power Automate. The book further deepens your proficiency in Power Apps by showing you how they can be used to extend the F&O functionality and incorporate artificial intelligence using AI Builder and its pre-trained AI models ready to use with your data. Throughout, you’ll gain a solid understanding of the diverse components of Power Platform and how they can transform your Dynamics 365 F&O experience.By the end of this book, you’ll be equipped with the skills and knowledge necessary to fully harness the immense potential of Power Platform and Dynamics 365 F&O.

Applied Supervised Learning with R. Use machine learning libraries of R to build models that solve business problems and predict future trends

Karthik Ramasubramanian, Jojo Moolayil

R provides excellent visualization features that are essential for exploring data before using it in automated learning.Applied Supervised Learning with R helps you cover the complete process of employing R to develop applications using supervised machine learning algorithms for your business needs. The book starts by helping you develop your analytical thinking to create a problem statement using business inputs and domain research. You will then learn different evaluation metrics that compare various algorithms, and later progress to using these metrics to select the best algorithm for your problem. After finalizing the algorithm you want to use, you will study the hyperparameter optimization technique to fine-tune your set of optimal parameters. The book demonstrates how you can add different regularization terms to avoid overfitting your model.By the end of this book, you will have gained the advanced skills you need for modeling a supervised machine learning algorithm that precisely fulfills your business needs.

Clean Code in C#. Refactor your legacy C# code base and improve application performance by applying best practices

Jason Alls

Traditionally associated with developing Windows desktop applications and games, C# is now used in a wide variety of domains, such as web and cloud apps, and has become increasingly popular for mobile development. Despite its extensive coding features, professionals experience problems related to efficiency, scalability, and maintainability because of bad code. Clean Code in C# will help you identify these problems and solve them using coding best practices.The book starts with a comparison of good and bad code, helping you understand the importance of coding standards, principles, and methodologies. You’ll then get to grips with code reviews and their role in improving your code while ensuring that you adhere to industry-recognized coding standards. This C# book covers unit testing, delves into test-driven development, and addresses cross-cutting concerns. You’ll explore good programming practices for objects, data structures, exception handling, and other aspects of writing C# computer programs. Once you’ve studied API design and discovered tools for improving code quality, you’ll look at examples of bad code and understand which coding practices you should avoid.By the end of this clean code book, you’ll have the developed skills you need in order to apply industry-approved coding practices to write clean, readable, extendable, and maintainable C# code.

Apache Spark for Data Science Cookbook. Solve real-world analytical problems

Padma Priya Chitturi

Spark has emerged as the most promising big data analytics engine for data science professionals. The true power and value of Apache Spark lies in its ability to execute data science tasks with speed and accuracy. Spark’s selling point is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. It lets you tackle the complexities that come with raw unstructured data sets with ease. This guide will get you comfortable and confident performing data science tasks with Spark. You will learn about implementations including distributed deep learning, numerical computing, and scalable machine learning. You will be shown effective solutions to problematic concepts in data science using Spark’s data science libraries such as MLLib, Pandas, NumPy, SciPy, and more. These simple and efficient recipes will show you how to implement algorithms and optimize your work.

Enterprise Security: A Data-Centric Approach to Securing the Enterprise. A guide to applying data-centric security concepts for securing enterprise data to enable an agile enterprise

Aaron Woody

Enterprise security redefined using a data-centric approach and trust models to transform information security into a business enablement process. It is a unique and forward thinking approach for deciding the best method to secure data in the enterprise, the cloud, and in BYOD environments.Enterprise Security: A Data-Centric Approach to Securing the Enterprise will guide you through redefining your security architecture to be more affective and turn information security into a business enablement process rather than a roadblock. This book will provide you with the areas where security must focus to ensure end-to-end security throughout the enterprise-supporting enterprise initiatives such as cloud and BYOD. Enterprise Security: A Data-Centric Approach to Securing the Enterprise will first introduce the reader to a new security architecture model and then explores the must have security methods and new tools that can used to secure the enterprise.This book will take a data-centric approach to securing the enterprise through the concept of Trust Models and building a layered security implementation focused on data. This is not your traditional security book focused on point solutions and the network aspect of security. This book combines best practice methods with new methods to approach enterprise security and how to remain agile as the enterprise demands more access to data from traditionally untrusted assets, hosted solutions, and third parties. Applied Information Security - A Data-Centric Approach to Securing the Enterprise will provide the reader an easy-to-follow flow from architecture to implementation, diagrams and recommended steps, and resources for further research and solution evaluation.This book is a reference and guide for all levels of enterprise security programs that have realized that non-data centric security is no longer practical and new methods must be used to secure the most critical assets in the enterprise.