This book is the official guide to Rust 2021, and this second edition has been fully updated to Rust’s latest version. Steve Klabnik and Carol Nichols, alumni of the Rust Core Team, share their knowledge to help you get the most out of Rust’s features so that you can create robust and scalable programs. In addition to numerous code examples, you’ll find three chapters dedicated to building complete projects: a number-guessing game, a Rust implementation of a command line tool, and a multithreaded server.

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This practical guide to Neo4j and the GDS library offers step-by-step explanations of essential concepts and practical instructions for implementing data science techniques on graph data using Neo4j version 5 and its associated libraries. Estelle Scifo starts by showing how to query Neo4j with Cypher and how to characterize graph datasets before moving on to the new and advanced capabilities of the GDS library that enable you to make predictions and write data science pipelines.

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This book is a friendly walkthrough to help readers build a first web application using Ruby and the Rails framework. Jonathan Evans uses the example of helping cats run a farm.

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This book is aimed at intermediate Swift developers who are familiar with writing asynchronous applications and who want to make use of the concurrency features Apple introduced in Swift 5.5. The Kodeco Team and Marin Todorov look at async/await, tasks and actors.

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The data mesh is a new way to decentralize data management, and in this book Jacek Majchrzak, Dr. Sven Balnojan and Dr. Marian Siwiak show how to start implementing a data mesh with flexible processes and organizational change, including both an extended case study and multiple real-world examples.

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In this book Adam Shostack delivers an easy-to-read and engaging discussion of security threats and how to develop secure systems. The book will prepare you to take on the Dark Side as you learn in a structured way about the threats to your systems.

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This book is actually eight books in one, with this edition updated for Java 19. Doug Lowe starts from the basics of Java, then goes deeper, with info on object-oriented programming, Java FX, Java web development, and beyond. Easy-to-follow instructions, fun practice, and a time-tested instructional approach are designed to shorten the learning journey.

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This book and its hands-on examples are designed to help you become proficient with Go for network automation. In this practical guide Nicolas Leiva and Michael Kashin teach how to automate common network operations and build systems using Go. After a general overview, use cases, strengths, and inherent weaknesses of Go the book continues with a deeper dive into network automation, exploring the common network automation areas and challenges, what language features are used in each of those areas, and the common software tools and packages.

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This book sets out to unlock the mysteries of theoretical physics by coding the underlying math in Haskell. Scott Walck shows how to use Haskell’s type system to check that your code makes sense. Walck explains Newtonian mechanics and electromagnetic theory, including how to describe and calculate electric and magnetic fields.

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This book is a pragmatic, hands-on guide to creating server-based web applications with Rust. Bastian Gruber shows how to work efficiently using pure Rust, along with important Rust libraries such as tokio for async runtimes, warp for web servers and APIs, and reqwest to run external HTTP requests.

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This book provides readers with a single-source reference to static-single assignment (SSA)-based compiler design. It is the first (and up to now only) book that covers in a deep and comprehensive way how an optimizing compiler can be designed using the SSA form. Edited by Fabrice Rastello and Florent Bouchez Tichadou the book has 24 chapters written by 31 authors and has been 12 years in the making.

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In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. In this book, Philipp Grohs and Gitta Kutyniok present the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field.

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