In the latest version of this programming language textbook,  Michael Scott takes the perspective that language design and language implementation are tightly interconnected, and that neither can be fully understood in isolation. In an approachable, readable style, he discusses more than 50 languages in the context of understanding how code is interpreted or compiled, providing an organizational framework for learning new languages, regardless of platform.

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This practical guide to optimization combines mathematical theory with hands-on coding examples to explore how Python can be used to model problems and obtain the best possible solutions. Krzysztof Postek et al present a balance of theory and practical applications. 

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Cruising Along with Java (Pragmatic Bookshelf)

This book, subtitled "Modernize and Modularize with the Latest Features" explains the changes to Java, from version 9 to 24, and shows how to apply new features to build enterprise applications faster and with fewer errors. Venkat Subramaniam explains how to get up to speed on how to make your code concise, expressive, and less error prone, and create better OO programs with the newest features. The book also shows how to modularize and create asynchronous applications with ease and proper error handling.

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This book shows how to to build graph neural networks for recommendation engines and molecular modeling.  TKeita Broadwater and Namid Stillman show how to both design and train models, and how to develop them into practical applications, with graph neural networks for node prediction, link prediction, and graph classification. The book includes coverage of the essential GNN libraries, including PyTorch Geometric, DeepGraph Library, and Alibaba’s GraphScope for training at scale.

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This book examines how Apple helped build China’s dominance in electronics assembly and manufacturing only to find itself trapped in a relationship with an authoritarian state making ever-increasing demands. Patrick McGee explains how after struggling to build its products on three continents, Apple was lured by China’s seemingly inexhaustible supply of cheap labor. 

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This fully revised third edition shows how to use Python to write programs that do in minutes what would take you hours to do by hand—no prior programming experience required. In early chapters Al Sweigart show the fundamentals of Python through clear explanations and engaging examples. From writing a first Python program, readers learn how to work with strings, lists, dictionaries, and other data structures; then use regular expressions to find and manipulate text patterns. Having mastered the basics, the book moves on to projects that teach how to use Python to automate tasks.

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The book presents practical guidance on state-of-the-art systems thinking methods and offers case study applications describing systems thinking methods in novel areas. Paul M. Salmon et al explain how to translate the outputs of systems thinking methods in practice and introduce systems thinking with an overview of human factors and ergonomics applications.

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This book looks at what it takes to design games from concept to completion. Alexia Mandeville, an experienced video game developer, explains the theory behind great gaming experiences, and the tools to bring game ideas to life. Choose the right game engines and design tools for any project and get step-by-step advice on testing and debugging the games you've made.

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Written for programmers with a background in another high-level language, in this book Harvey Deitel teaches modern Java development hands on using the latest Java idioms and features and genAIs. In the context of 200+ real-world code examples, readers begin with Java fundamentals then move on to arrays, strings, regular expressions, JSON/CSV processing with the Jackson library.

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This book covers the essential mathematics that will take you from basic coding to serious software development. Ronald T. Kneusel shows how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms.

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This book asks the question "Can you trust results from modeling and simulation?" and provides a framework for assessing the reliability of and uncertainty included in the results used by decision makers and policy makers in industry and government. The emphasis is on models described by PDEs and their numerical solution. William L. Oberkampf and Christopher J. Roy consider procedures and results from all aspects of verification and validation, integrated with modern methods in uncertainty quantification and stochastic simulation.

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Web browsers are the most common and widely-used platform  for code to run on. In this book Pavel Panchekha and Chris Harrelson describe how they work and how that impacts web developers and other software engineers whose work touches the web. The authors build their own web browser, including rich visual effects, multithreaded architecture, JavaScript APIs, and comprehensive security policies, and explore the challenges, interesting algorithms, and clever optimizations this entails.

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