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Podcasts
Reading, navigating, and debugging a large frontend codebase is a major issue faced by frontend developers. This book is designed to help web developers like you learn about ReactJS and TypeScript, both of which power large-scale apps for many organizations.This second edition of Learn React with TypeScript is updated, enhanced, and improved to cover new features of React 18 including hooks, state management libraries, and features of TypeScript 4. The book will enable you to create well-structured and reusable React components that are easy to read and maintain, leveraging modern design patterns.You’ll be able to ensure that all your components are type-safe, making the most of TypeScript features, including some advanced types. You’ll also learn how to manage complex states using Redux and how to interact with a GraphQL web API. Finally, you’ll discover how to write robust unit tests for React components using Jest.By the end of the book, you’ll be well-equipped to use both React and TypeScript.
Most organizations exhibit a time-dependent structure in their processes, including fields such as finance. By leveraging time series analysis and forecasting, these organizations can make informed decisions and optimize their performance. Accurate forecasts help reduce uncertainty and enable better planning of operations. Unlike traditional approaches to forecasting, deep learning can process large amounts of data and help derive complex patterns. Despite its increasing relevance, getting the most out of deep learning requires significant technical expertise.This book guides you through applying deep learning to time series data with the help of easy-to-follow code recipes. You’ll cover time series problems, such as forecasting, anomaly detection, and classification. This deep learning book will also show you how to solve these problems using different deep neural network architectures, including convolutional neural networks (CNNs) or transformers. As you progress, you’ll use PyTorch, a popular deep learning framework based on Python to build production-ready prediction solutions.By the end of this book, you'll have learned how to solve different time series tasks with deep learning using the PyTorch ecosystem.
Hands-On Azure Digital Twins. A practical guide to building distributed IoT solutions
In today’s world, clients are using more and more IoT sensors to monitor their business processes and assets. Think about collecting information such as pressure in an engine, the temperature, or a light switch being turned on or off in a room. The data collected can be used to create smart solutions for predicting future trends, creating simulations, and drawing insights using visualizations. This makes it beneficial for organizations to make digital twins, which are digital replicas of the real environment, to support these smart solutions.This book will help you understand the concept of digital twins and how it can be implemented using an Azure service called Azure Digital Twins. Starting with the requirements and installation of the Azure Digital Twins service, the book will explain the definition language used for modeling digital twins. From there, you'll go through each step of building digital twins using Azure Digital Twins and learn about the different SDKs and APIs and how to use them with several Azure services. Finally, you'll learn how digital twins can be used in practice with the help of several real-world scenarios.By the end of this book, you'll be confident in building and designing digital twins and integrating them with various Azure services.
With Jetpack libraries, you can build and design high-quality, robust Android apps that have an improved architecture and work consistently across different versions and devices. This book will help you understand how Jetpack allows developers to follow best practices and architectural patterns when building Android apps while also eliminating boilerplate code.Developers working with Android and Kotlin will be able to put their knowledge to work with this condensed practical guide to building apps with the most popular Jetpack libraries, including Jetpack Compose, ViewModel, Hilt, Room, Paging, Lifecycle, and Navigation. You'll get to grips with relevant libraries and architectural patterns, including popular libraries in the Android ecosystem such as Retrofit, Coroutines, and Flow while building modern applications with real-world data.By the end of this Android app development book, you'll have learned how to leverage Jetpack libraries and your knowledge of architectural concepts for building, designing, and testing robust Android applications for various use cases.
Florian Rappl, Lothar Schöttner
The organizational pattern of micro frontends allows you to split web applications into multiple parts, where each part can be owned by an autonomous team. Each team can have its own development and deployment life cycle, allowing every part of an application to be shipped in isolation. Following the strategies outlined in this book, you can avoid complexity while increasing resilience for your frontend. This updated second edition will guide you through the patterns available to implement a micro frontend solution. You’ll learn about micro frontends, the different architecture styles, and their areas of use. Then, you’ll learn how to prepare teams for the change to micro frontends, as well as how to adjust the user interface (UI) design and your CSS styles for scalability. Starting with the simplest variants of micro frontend architectures, the book progresses from static approaches to fully dynamic solutions that allow maximum scalability with faster release cycles. In the concluding chapters, you’ll strengthen the security level of your micro frontend solution, while reinforcing your overall knowledge with real-world case studies relating to micro frontends. By the end of this book, you’ll be able to decide whether and how micro frontends should be implemented to achieve high scalability for your web app.
Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI).You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs.Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system.By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications.This Learning Path includes content from the following Packt products:• Julia 1.0 Programming - Second Edition by Ivo Balbaert• Julia Programming Projects by Adrian Salceanu
Learn T-SQL Querying. A guide to developing efficient and elegant T-SQL code - Second Edition
Data professionals seeking to excel in Transact-SQL for Microsoft SQL Server and Azure SQL Database often lack comprehensive resources. Learn T-SQL Querying second edition focuses on indexing queries and crafting elegant T-SQL code enabling data professionals gain mastery in modern SQL Server versions (2022) and Azure SQL Database. The book covers new topics like logical statement processing flow, data access using indexes, and best practices for tuning T-SQL queries.Starting with query processing fundamentals, the book lays a foundation for writing performant T-SQL queries. You’ll explore the mechanics of the Query Optimizer and Query Execution Plans, learning to analyze execution plans for insights into current performance and scalability. Using dynamic management views (DMVs) and dynamic management functions (DMFs), you’ll build diagnostic queries. The book covers indexing and delves into SQL Server’s built-in tools to expedite resolution of T-SQL query performance and scalability issues. Hands-on examples will guide you to avoid UDF pitfalls and understand features like predicate SARGability, Query Store, and Query Tuning Assistant. By the end of this book, you‘ll have developed the ability to identify query performance bottlenecks, recognize anti-patterns, and avoid pitfalls