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 appl...

This book offers a comprehensive exploration of the intersection between Large Language Models (LLMs) and recommendation systems, serving as a practical guide for practitioners, researchers, and students in AI, natural language processing, and data science. It addresses the limitations of traditional recommendation techniques—such as their inability to fully understand nuanced language, reason dynamically over user preferences, or leverage multi-modal data—and demonstrates how LLMs can rev...

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. Topi...

Stay one step ahead of your competitors with proven tips, strategies, and insights from over 30 Kaggle Masters and Grandmasters and become a better data scientist. This new edition features updated content and new chapters on Kaggle Models, time series, and Generative AI competitions. Key FeaturesLearn how Kaggle works to make the most of every competition with winning strategies from 30+ expert KagglersSharpen your modeling skills with feature engineer...

Let Peng Shao, a former engineering leader at Amazon and Staff ML Engineer at Twitter, be your guide to mastering Machine Learning interviews in this comprehensive 314-page resource.Inside, you'll find:. Comprehensive breakdown of the ML interview process, including all the major interview sessions: ML Fundamentals, ML Coding, ML System Design, & ML Infrastructure.. Proven strategies for approaching ...

The multidisciplinary field of quantum computing strives to exploit some of the uncanny aspects of quantum mechanics to expand our computational horizons. Quantum Computing for Computer Scientists takes readers on a tour of this fascinating area of cutting-edge research. Written in an accessible yet rigorous fashion, this book employs ideas and techniques familiar to every student of computer science. The reader is not expected to have any advanced mathematics or physics background. After ...

Build effective RESTful APIs for enterprise with design patterns and REST framework's out-of-the-box capabilitiesKey FeaturesUnderstand advanced topics such as API gateways, API securities, and cloudImplement patterns programmatically with easy-to-follow examplesModernize legacy codebase using API connectors, layers, and microservicesBook DescriptionThis book deals with the Representational State Transfer (REST) paradigm, whi...

Coding and computational thinking (the ability to think like a computer) are among the skills that will serve students well in the future. Coding goes beyond websites and software – it’s an essential component in finding solutions to everyday problems. Computational thinking has many applications beyond the computer lab or math class –it teaches reasoning, creativity and expression, and is an innovative way to demonstrate content knowledge and see mathematical processes in action.

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students.The book outlines the shortest possible path from no previous experience with programming to a set of skills that...

Learn to be deliberate and intentional in your design, technology, and pattern choices when developing an application using a microservices architecture.Key FeaturesTackle common design problems when developing a microservices application using .NET CoreExplore applying S.O.L.I.D development principles in developing a stable microservice applicationUse your knowledge to solve common microservice application design challengesBook D...

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows...

Architect your .NET applications by breaking them into really small pieces - microservices -using this practical, example-based guide. Key Features\[\*\]Start your microservices journey and get a broader perspective on microservices development using C\# 7.0 with .NET Core 2.0\[\*\]Build, deploy, and test microservices using ASP.Net Core, ASP.NET Core API, and Microsoft Azure Cloud\[\*\]Get the basics of reactive microservicesBook...