Jay Wang – författare

Computational Modeling, by Jay Wang introduces computational modeling and visualization of physical systems that are commonly found in physics and related areas. The authors begin with a framework that integrates model building, algorithm development, and data visualization for problem solving via scientific computing. Through carefully selected problems, methods, and projects, the reader is guided to learning and discovery by actively doing rather than just knowing physics.

Unlock Java''s full potential for cloud computing through expert insights from real-world case studies and stay ahead with the latest trends in agile and robust Java application development

Key Features

Master concurrency and parallelism to overcome cloud computing challenges in JavaBuild scalable solutions with Big Data, ML, microservices, and serverless architecturesExplore cloud scaling, GPU utilization, and future tech innovations in Java applicationsPurchase of the print or Kindle book includes a free PDF eBook

Book Description

If you’re a software developer, architect, or systems engineer, exploring Java’s concurrency utilities and synchronization in the cloud, this book is an essential resource. Tech visionary Jay Wang, with over three decades of experience transforming industry giants, brings unparalleled expertise to guide you through Java’s concurrency and parallel processing in cloud computing.This comprehensive book starts by establishing the foundational concepts of concurrency and parallelism, vital for cloud-native development, and gives you a complete overview, highlighting challenges and best practices. Wang expertly demonstrates Java’s role in big data, machine learning, microservices, and serverless computing, shedding light on how Java’s tools are effectively utilized in these domains. Complete with practical examples and insights, this book bridges theory with real-world applications, ensuring a holistic understanding of Java in cloud-based scenarios. You’ll navigate advanced topics, such as synchronizing Java’s concurrency with cloud auto-scaling and GPU computing, and be equipped with the skills and foresight to tackle upcoming trends in cloud technology.This book serves as your roadmap to innovation and excellence in Java cloud applications, giving you in-depth knowledge and hands-on practice for mastering Java in the cloud era.

What you will learn

Understand Java concurrency in cloud app developmentGet to grips with the core concepts of serverless computing in JavaBoost cloud scaling and performance using Java skillsImplement Java GPU acceleration for advanced computing tasksGain insights into Java''s role in the evolving cloud and AI technologyAccess hands-on exercises for real-world Java applicationsExplore diverse Java case studies in tech and fintechImplement Java in AI-driven cloud and data workflowsAnalyze Java''s application in IoT and real-time analytics

Who this book is for

This book is for Java developers, software engineers, and cloud architects with intermediate Java knowledge. It''s ideal for professionals transitioning to cloud-native development or seeking to enhance their concurrent programming skills. DevOps engineers and tech leads involved in cloud migration will also find valuable insights. Basic Java proficiency, familiarity with cloud concepts, and some experience with distributed systems is expected.

Unlock Java's full potential for cloud computing through expert insights from real-world case studies and stay ahead with the latest trends in agile and robust Java application developmentKey FeaturesMaster concurrency and parallelism to overcome cloud computing challenges in JavaBuild scalable solutions with Big Data, ML, microservices, and serverless architecturesExplore cloud scaling, GPU utilization, and future tech innovations in Java applicationsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIf you’re a software developer, architect, or systems engineer, exploring Java’s concurrency utilities and synchronization in the cloud, this book is an essential resource. Tech visionary Jay Wang, with over three decades of experience transforming industry giants, brings unparalleled expertise to guide you through Java’s concurrency and parallel processing in cloud computing.This comprehensive book starts by establishing the foundational concepts of concurrency and parallelism, vital for cloud-native development, and gives you a complete overview, highlighting challenges and best practices. Wang expertly demonstrates Java’s role in big data, machine learning, microservices, and serverless computing, shedding light on how Java’s tools are effectively utilized in these domains. Complete with practical examples and insights, this book bridges theory with real-world applications, ensuring a holistic understanding of Java in cloud-based scenarios. You’ll navigate advanced topics, such as synchronizing Java’s concurrency with cloud auto-scaling and GPU computing, and be equipped with the skills and foresight to tackle upcoming trends in cloud technology.This book serves as your roadmap to innovation and excellence in Java cloud applications, giving you in-depth knowledge and hands-on practice for mastering Java in the cloud era.What you will learnUnderstand Java concurrency in cloud app developmentGet to grips with the core concepts of serverless computing in JavaBoost cloud scaling and performance using Java skillsImplement Java GPU acceleration for advanced computing tasksGain insights into Java's role in the evolving cloud and AI technologyAccess hands-on exercises for real-world Java applicationsExplore diverse Java case studies in tech and fintechImplement Java in AI-driven cloud and data workflowsAnalyze Java's application in IoT and real-time analyticsWho this book is forThis book is for Java developers, software engineers, and cloud architects with intermediate Java knowledge. It's ideal for professionals transitioning to cloud-native development or seeking to enhance their concurrent programming skills. DevOps engineers and tech leads involved in cloud migration will also find valuable insights. Basic Java proficiency, familiarity with cloud concepts, and some experience with distributed systems is expected.

This book provides a practical and comprehensive introduction to computational problem solving from the viewpoints of practitioners in both academic and industrial worlds.  The authors present scientific problem-solving using computation and aim to increase computational thinking, which is the mindset and skillset required to solve scientific problems with computational methodologies via model building, simulation, data analysis, and visualization using the Python programming language.  Topics and examples span fundamental areas of physical science as well as contemporary topics including quantum computing, neural networks, machine learning, global warming, and energy balance. The book features unique and innovative techniques and practices including: intentional scaffolding to help beginners learn computational problem solving; multimodal computing environments including cloud-based platforms and just-in-time computing; emphasis and connection between both numerical and symbolic computations; and extensive exercise sets carefully designed for further exploration as project assignments or self-paced study.  The book is suitable for introductory level readers in physical sciences, engineering, and related STEM disciplines. Specifically, the book is appropriate for use in either a standalone course on computation and modeling and as a resource for readers interested in learning about proven techniques in interactive computing.

This book provides a practical and comprehensive introduction to computational problem solving from the viewpoints of practitioners in both academic and industrial worlds.  The authors present scientific problem-solving using computation and aim to increase computational thinking, which is the mindset and skillset required to solve scientific problems with computational methodologies via model building, simulation, data analysis, and visualization using the Python programming language.  Topics and examples span fundamental areas of physical science as well as contemporary topics including quantum computing, neural networks, machine learning, global warming, and energy balance. The book features unique and innovative techniques and practices including: intentional scaffolding to help beginners learn computational problem solving; multimodal computing environments including cloud-based platforms and just-in-time computing; emphasis and connection between both numerical and symbolic computations; and extensive exercise sets carefully designed for further exploration as project assignments or self-paced study.  The book is suitable for introductory level readers in physical sciences, engineering, and related STEM disciplines. Specifically, the book is appropriate for use in either a standalone course on computation and modeling and as a resource for readers interested in learning about proven techniques in interactive computing.