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Podcasts
iPhone User Interface Cookbook. A concise dissection of Apple’s iOS user interface design principles
The incredible growth rates for the iPhone, iPod touch, and iPad have pushed consumers to a new “App” economy, with developers racing to the platform. Mobile touch-centric interfaces vary greatly from traditional computing platforms, and programmers as well as designers must learn to adapt to the new form-factor.The iPhone User Interface Cookbook offers a complete breakdown of standard interface design on the iPhone, iPod touch, and iPad. You will learn the tools behind the trade, how to properly utilize standard interface elements, and custom UI tricks that will help your work stand out on the App Store.The book is designed to be a complete overview of interface design on all iOS platforms, offering insight and an inside look into app design. A variety of topics are covered, starting with an overview of tools for the app interface designer, touching upon popular interface components such as the Tab Bar, and offering suggestions for complex game interfaces. Whether you’re new to the platform or a seasoned developer with numerous applications in the App Store, this book strives to teach everyone simple and easy to implement tips for iOS interface design. Regardless of skill level, the iPhone User Interface Cookbook offers a detailed breakdown of all things interface design.
While machine learning is not new, it's only now that we are beginning to uncover its true potential in the healthcare and life sciences industry. The availability of real-world datasets and access to better compute resources have helped researchers invent applications that utilize known AI techniques in every segment of this industry, such as providers, payers, drug discovery, and genomics.This book starts by summarizing the introductory concepts of machine learning and AWS machine learning services. You’ll then go through chapters dedicated to each segment of the healthcare and life sciences industry. Each of these chapters has three key purposes -- First, to introduce each segment of the industry, its challenges, and the applications of machine learning relevant to that segment. Second, to help you get to grips with the features of the services available in the AWS machine learning stack like Amazon SageMaker and Amazon Comprehend Medical. Third, to enable you to apply your new skills to create an ML-driven solution to solve problems particular to that segment. The concluding chapters outline future industry trends and applications.By the end of this book, you’ll be aware of key challenges faced in applying AI to healthcare and life sciences industry and learn how to address those challenges with confidence.
Elevate your practical C# and .NET skills to the next level with this new edition of Apps and Services with .NET 8.With chapters that put a variety of technologies into practice, including Web API, gRPC, GraphQL, and SignalR, this book will give you a broader scope of knowledge than other books that often focus on only a handful of .NET technologies. You’ll dive into the new unified model for Blazor Full Stack and leverage .NET MAUI to develop mobile and desktop apps.This new edition introduces the latest enhancements, including the seamless implementation of web services with ADO.NET SqlClient's native Ahead-of-Time (AOT) support. Popular library coverage now includes Humanizer and Noda Time. There’s also a brand-new chapter that delves into service architecture, caching, queuing, and robust background services.By the end of this book, you’ll have a wide range of best practices and deep insights under your belt to help you build rich apps and efficient services.
Exam Ref AZ-104 Microsoft Azure Administrator Certification and Beyond covers all the exam objectives and will help you to earn the Microsoft Azure Administrator certification with ease. Whether you’re studying to pass the AZ-104 exam or just want hands-on experience in administering Azure, this AZ-104 study guide will help you to achieve your objectives.This book covers the latest Azure features and capabilities around configuring, managing, and securing Azure resources. Adhering to Microsoft's AZ-104 exam syllabus, this guide is divided into five modules. The first module will show you how to manage Azure identities and governance. You'll find out how to configure Azure subscription policies at the Azure subscription level and use Azure policies for resource groups. After that, the book covers techniques related to implementing and managing storage in Azure, enabling you to create and manage Azure Storage, including File and Blob storage. In the second module, you’ll learn how to deploy and manage Azure compute resources. The third and fourth modules will teach you about configuring and managing virtual networks and monitoring and backing up Azure resources. Finally, you'll work through mock tests, with answers provided, to prepare for this exam.By the end of this book, you'll have the skills needed to pass the AZ-104 exam and be able to expertly manage Azure.
Luca Zavarella, Francesca Lazzeri
Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages.You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model.By the end of this book, you’ll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R.
DevOps and the cloud revolution have forced software engineers and operations teams to rethink how to manage infrastructures. With this AWS book, you'll understand how you can use Infrastructure as Code (IaC) to simplify IT operations and manage the modern cloud infrastructure effectively with AWS CloudFormation.This comprehensive guide will help you explore AWS CloudFormation from template structures through to developing complex and reusable infrastructure stacks. You'll then delve into validating templates, deploying stacks, and handling deployment failures. The book will also show you how to leverage AWS CodeBuild and CodePipeline to automate resource delivery and apply continuous integration and continuous delivery (CI/CD) practices to the stack. As you advance, you'll learn how to generate templates on the fly using macros and create resources outside AWS with custom resources. Finally, you'll improve the way you manage the modern cloud in AWS by extending CloudFormation using AWS serverless application model (SAM) and AWS cloud development kit (CDK).By the end of this book, you'll have mastered all the major AWS CloudFormation concepts and be able to simplify infrastructure management.
In this digitally driven era, safeguarding against relentless cyber threats is non-negotiable. This guide will enable you to enhance your skills as a digital forensic examiner by introducing you to cyber challenges that besiege modern entities. It will help you to understand the indispensable role adept digital forensic experts play in preventing these threats and equip you with proactive tools to defend against ever-evolving cyber onslaughts.The book begins by unveiling the intricacies of Windows operating systems and their foundational forensic artifacts, helping you master the art of streamlined investigative processes. From harnessing opensource tools for artifact collection to delving into advanced analysis, you’ll develop the skills needed to excel as a seasoned forensic examiner. As you advance, you’ll be able to effortlessly amass and dissect evidence to pinpoint the crux of issues. You’ll also delve into memory forensics tailored for Windows OS, decipher patterns within user data, and log and untangle intricate artifacts such as emails and browser data.By the end of this book, you’ll be able to robustly counter computer intrusions and breaches, untangle digital complexities with unwavering assurance, and stride confidently in the realm of digital forensics.
Brij Kishore Pandey, Emily Ro Schoof
Modern extract, transform, and load (ETL) pipelines for data engineering have favored the Python language for its broad range of uses and a large assortment of tools, applications, and open source components. With its simplicity and extensive library support, Python has emerged as the undisputed choice for data processing.In this book, you’ll walk through the end-to-end process of ETL data pipeline development, starting with an introduction to the fundamentals of data pipelines and establishing a Python development environment to create pipelines. Once you've explored the ETL pipeline design principles and ET development process, you'll be equipped to design custom ETL pipelines. Next, you'll get to grips with the steps in the ETL process, which involves extracting valuable data; performing transformations, through cleaning, manipulation, and ensuring data integrity; and ultimately loading the processed data into storage systems. You’ll also review several ETL modules in Python, comparing their pros and cons when building data pipelines and leveraging cloud tools, such as AWS, to create scalable data pipelines. Lastly, you’ll learn about the concept of test-driven development for ETL pipelines to ensure safe deployments.By the end of this book, you’ll have worked on several hands-on examples to create high-performance ETL pipelines to develop robust, scalable, and resilient environments using Python.