Scalable Ai And Design Patterns
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Scalable Ai And Design Patterns
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Author : Abhishek Mishra
language : en
Publisher: Springer Nature
Release Date : 2024-03-11
Scalable Ai And Design Patterns written by Abhishek Mishra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-11 with Computers categories.
Understand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's needs and drive innovation in the era of intelligent automation. This book begins with an overview of scalable AI systems and the importance of design patterns in creating robust intelligent solutions. It covers fundamental concepts and techniques for achieving scalability in AI systems, including data engineering practices and strategies. The book also addresses scalable algorithms, models, infrastructure, and architecture considerations. Additionally, it discusses deployment, productionization, real-time and streaming data, edge computing, governance, and ethics in scalable AI. Real-world case studies and best practices are presented, along with insights into future trends and emerging technologies. The book focuses on scalable AI and design patterns, providing an understanding of the challenges involved in developing AI systems that can handle large amounts of data, complex algorithms, and real-time processing. By exploring scalability, you will be empowered to design and implement AI solutions that can adapt to changing data requirements. What You Will Learn Develop scalable AI systems that can handle large volumes of data, complex algorithms, and real-time processing Know the significance of design patterns in creating robust intelligent solutions Understand scalable algorithms and models to handle extensive data and computing requirements and build scalable AI systems Be aware of the ethical implications of scalable AI systems Who This Book Is For AI practitioners, data scientists, and software engineers with intermediate-level AI knowledge and experience
Scalable Artificial Intelligence Systems Cloud Native Edge Ai Mlops And Governance For Real World Deployment
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Author : Swarup Panda
language : en
Publisher: Deep Science Publishing
Release Date : 2025-07-28
Scalable Artificial Intelligence Systems Cloud Native Edge Ai Mlops And Governance For Real World Deployment written by Swarup Panda and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-28 with Computers categories.
Artificial Intelligence (AI) has become essential across industries, transforming operations, decision-making, and value creation. As organizations worldwide use AI to address challenges in areas like healthcare, finance, cybersecurity, manufacturing, and infrastructure, the need for reliable and scalable AI systems continues to grow. This book offers practical guidance for professionals designing and deploying scalable, compliant AI solutions in production environments. It covers modernizing legacy systems, building MLOps pipelines, and addressing ethical aspects of autonomous AI, providing essential insights and patterns for real-world applications. We cover essential topics for enterprise AI success, such as scalable architectures (cloud-native, edge, hybrid), MLOps for lifecycle management, and governance for compliance and fairness. The text also outlines frameworks for explainable and federated AI in regulated fields, supporting privacy and distributed intelligence. We demonstrate AI's impact on diagnostics, fraud detection, threat intelligence, and urban planning through case studies, and review how platforms like Azure, AWS, and GCP support scalable AI deployment. This book highlights the need for ethical AI that upholds human values, privacy, and transparency. As AI shapes society, we must design, deploy, and govern it responsibly. I invite you to explore these chapters with a mindset of both innovation and accountability—as together, we shape a future powered by intelligent and responsible systems.
Mastering Design Patterns In Java
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Author : Aditya Pratap Bhuyan
language : en
Publisher: Aditya Pratap Bhuyan
Release Date : 2024-10-15
Mastering Design Patterns In Java written by Aditya Pratap Bhuyan and has been published by Aditya Pratap Bhuyan this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-15 with Computers categories.
"Mastering Design Patterns in Java: Building Robust and Scalable Software" is your ultimate guide to understanding and implementing design patterns in Java. Whether you're a seasoned developer or just starting your journey with Java, this book equips you with the knowledge and practical skills to tackle software design challenges using well-established, time-tested solutions. Design patterns provide proven approaches to common problems in software design, making code more efficient, reusable, and scalable. This book delves deep into the three main categories of design patterns—Creational, Structural, and Behavioral—offering hands-on examples and practical guidance for each. Patterns such as Singleton, Factory, Adapter, Observer, and many more are explained in detail, with code examples specifically tailored to Java. By the end of each chapter, you’ll not only understand the theoretical underpinnings of each pattern but also know how to apply them effectively in real-world projects. In addition to covering core design patterns, this book takes a step further by addressing advanced topics such as anti-patterns (common pitfalls to avoid), combining patterns in large-scale systems, and using design patterns in cloud-based and microservices architectures. Java developers working on distributed systems, cloud infrastructure, or modern applications will find valuable insights into how design patterns can improve code organization and maintainability. The book’s practical approach ensures that you can immediately start implementing the patterns in your own projects. With exercises, examples, and in-depth explanations, it’s an invaluable resource for any developer looking to improve their software design skills. Whether you're building small applications or architecting large systems, Mastering Design Patterns in Java will help you write clean, modular, and scalable code, positioning you for success in today’s fast-evolving software development landscape. Let this book be your guide to mastering the art of design patterns in Java.
The Cloud Architect S Playbook Scaling Enterprise Systems With Databases Ai And Performance Driven Design 2025
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Author : Author1: ARNAB SAHA, Author2 DR LALIT KUMAR
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
The Cloud Architect S Playbook Scaling Enterprise Systems With Databases Ai And Performance Driven Design 2025 written by Author1: ARNAB SAHA, Author2 DR LALIT KUMAR and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In today’s digital landscape, organizations must deliver reliable, high-performance experiences at an ever-increasing scale. As enterprises embrace cloud-native technologiesmicroservices, container orchestration, managed data platforms, and AI-driven insightsthey confront a new set of architectural challenges. How do you design distributed systems that remain resilient in the face of variable load, regional outages, and shifting business requirements? How can databases, caches, and streaming pipelines be orchestrated to support both real-time decisioning and deep historical analysis? And how can teams embed observability, governance, and cost-effectiveness into every layer of their infrastructure? The Cloud Architect’s Playbook guides you through these questions by distilling years of lessons learned at the forefront of cloud engineering. We begin by laying the foundations of scalable architectureelasticity, fault tolerance, and performance-driven observabilitybefore diving into data strategies that leverage polyglot persistence, data lakes, and streaming systems. From there, we explore how to build AI-native applications that continuously learn from live traffic and integrate seamlessly into microservice environments. Throughout, we emphasize design patterns that isolate failure domains, enforce consistency trade-offs wisely, and enable graceful degradation under stress. More than a catalog of technologies, this playbook offers a holistic mindset: one that treats infrastructure as code, data as a product, and performance as a first-class citizen. Each chapter closes with guiding principles, concrete examples, and “play calls”actionable recommendations for choosing the right pattern in your context. We highlight not only the “what” and the “how,” but also the “why,” helping you weigh trade-offs in cost, complexity, and risk. Whether you’re a seasoned cloud architect, a data engineer stepping into system design, or an engineering leader responsible for cross-functional initiatives, this book equips you with the frameworks, patterns, and
Architecting Intelligent Cloud Systems Ai Mlops And Scalable Infrastructure For The Future
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Author : PHANISH LAKKARASU
language : en
Publisher: Global Pen Press UK PUBLICATION
Release Date :
Architecting Intelligent Cloud Systems Ai Mlops And Scalable Infrastructure For The Future written by PHANISH LAKKARASU and has been published by Global Pen Press UK PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Architecture categories.
Llm Design Patterns
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Author : Ken Huang
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-30
Llm Design Patterns written by Ken Huang and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Computers categories.
Explore reusable design patterns, including data-centric approaches, model development, model fine-tuning, and RAG for LLM application development and advanced prompting techniques Key Features Learn comprehensive LLM development, including data prep, training pipelines, and optimization Explore advanced prompting techniques, such as chain-of-thought, tree-of-thought, RAG, and AI agents Implement evaluation metrics, interpretability, and bias detection for fair, reliable models Print or Kindle purchase includes a free PDF eBook Book DescriptionThis practical guide for AI professionals enables you to build on the power of design patterns to develop robust, scalable, and efficient large language models (LLMs). Written by a global AI expert and popular author driving standards and innovation in Generative AI, security, and strategy, this book covers the end-to-end lifecycle of LLM development and introduces reusable architectural and engineering solutions to common challenges in data handling, model training, evaluation, and deployment. You’ll learn to clean, augment, and annotate large-scale datasets, architect modular training pipelines, and optimize models using hyperparameter tuning, pruning, and quantization. The chapters help you explore regularization, checkpointing, fine-tuning, and advanced prompting methods, such as reason-and-act, as well as implement reflection, multi-step reasoning, and tool use for intelligent task completion. The book also highlights Retrieval-Augmented Generation (RAG), graph-based retrieval, interpretability, fairness, and RLHF, culminating in the creation of agentic LLM systems. By the end of this book, you’ll be equipped with the knowledge and tools to build next-generation LLMs that are adaptable, efficient, safe, and aligned with human values. What you will learn Implement efficient data prep techniques, including cleaning and augmentation Design scalable training pipelines with tuning, regularization, and checkpointing Optimize LLMs via pruning, quantization, and fine-tuning Evaluate models with metrics, cross-validation, and interpretability Understand fairness and detect bias in outputs Develop RLHF strategies to build secure, agentic AI systems Who this book is for This book is essential for AI engineers, architects, data scientists, and software engineers responsible for developing and deploying AI systems powered by large language models. A basic understanding of machine learning concepts and experience in Python programming is a must.
Scalable Artificial Intelligence For Healthcare
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Author : Houneida Sakly
language : en
Publisher: CRC Press
Release Date : 2025-05-06
Scalable Artificial Intelligence For Healthcare written by Houneida Sakly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-06 with Computers categories.
This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility. The content provides a comprehensive exploration of the principles and practices required to scale AI applications in healthcare, addressing areas such as diagnosis, treatment, and patient care. Key topics include data scalability, model deployment, and infrastructure design, highlighting the use of microservices, containerization, cloud computing, and big data technologies in building scalable AI systems. Discussions cover advancements in machine learning models, distributed processing, and transfer learning, alongside critical considerations such as continuous integration, data privacy, and ethics. Real-world case studies depict both the successes and challenges of implementing scalable AI across various healthcare environments, offering valuable insights for future advancements. This volume serves as a practical and theoretical guide for healthcare professionals, AI researchers, and technology enthusiasts seeking to develop or expand on AI-driven healthcare solutions to address global health challenges effectively.
Mastering Serverless Computing With Aws Lambda Unlock Scalability Optimize Costs And Drive Innovation With Aws Lambda Serverless Solutions For Modern Cloud Transformation
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Author : Eidivandi Omid
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-11-14
Mastering Serverless Computing With Aws Lambda Unlock Scalability Optimize Costs And Drive Innovation With Aws Lambda Serverless Solutions For Modern Cloud Transformation written by Eidivandi Omid and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-14 with Computers categories.
Design and Build Scalable Solutions on the AWS Serverless Ecosystem. Key Features● In-depth exploration of AWS Lambda Integration within serverless architecture.● Expert tips and guidance on choosing compute services for peak performance.● Practical Techniques for achieving observability, governance, and reliability. Book DescriptionAWS Lambda, a key component of AWS Serverless Computing, has transformed application development by allowing developers to focus on code rather than infrastructure. [Mastering Serverless Computing with AWS Lambda] is a must-have guide for leveraging AWS Lambda to build efficient, cost-effective serverless cloud solutions. This book guides readers from serverless basics to advanced deployment, offering practical approaches to building resilient, scalable applications. Beginning with an introduction to serverless computing, the book explores AWS Lambda fundamentals, covering invocation models, service integrations, and event-driven design. Practical insights into hyper-scaling, instrumentation, and designing for failure empower readers to create robust, production-ready solutions. This guide covers core concepts of serverless computing, including optimizations, automation, and strategies to navigate potential pitfalls. It emphasizes AWS Lambda’s resiliency, scalability, and disaster recovery, using real-world examples to showcase best practices. Each chapter offers in-depth examples, edge computing scenarios, and proven patterns to help readers develop optimized serverless architectures. By the end, readers will gain a comprehensive understanding of AWS Lambda, equipping them to design sophisticated systems that meet modern cloud demands and drive innovation within their organizations. What you will learn● Gain a solid understanding of serverless architecture and how AWS Lambda fits into the serverless ecosystem.● Learn the core components of AWS Lambda, from function creation and triggers to its role in cloud-native development.● Discover techniques for leveraging Lambda’s automatic scaling to handle fluctuating workloads while optimizing costs.● Learn best practices for creating resilient Lambda functions designed to withstand failures and ensure high availability.● Apply industry-tested patterns, architectural best practices, and real-world scenarios to build robust, scalable, and cost-effective serverless applications with AWS Lambda. Table of Contents1. Introduction to Serverless Computing2. AWS Lambda Basics3. Invocation Models and Service Integrations4. Event-Driven Design with Lambda5. Hyper-Scaling with Lambda6. Instrumenting Lambda7. Resiliency and Design for Failure8. Lambda-Less Design9. Edge Computing10. Patterns and Practices Index
Ai And Microservices
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Author : Dileep Kumar Pandiya
language : en
Publisher: Springer Nature
Release Date : 2025-07-01
Ai And Microservices written by Dileep Kumar Pandiya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.
This book explores how artificial intelligence (AI) is transforming the design and operation of microservices and API architecture. It provides a clear and practical guide to using AI to automate tasks, enhance performance, and improve the scalability of microservice-based systems. Starting with the basics, you will learn about the core concepts of microservices and API design, gradually building an understanding of how AI can be seamlessly integrated. Through real-world examples, visual diagrams, and mock APIs, the book shows you how to bring theory into practice, making complex systems easier to manage and more efficient. You will also discover strategies for testing and scaling systems, securing APIs, and addressing ethical challenges in AI-powered environments. Case studies highlight successful implementations, offering valuable insights you can apply to your own projects. Whether you're a developer, architect, or tech enthusiast, this book gives you the tools and inspiration to build smarter, more resilient systems while staying ahead of future trends in AI and distributed computing. What You'll Learn: Understand the basics of microservices and API design and see how AI can make these systems smarter and more efficient. Discover how to use AI in microservices and APIs to automate tasks, improve performance, and boost security. Learn how to design scalable and secure systems by following best practices and innovative approaches. Get practical tips on troubleshooting and solving challenges in AI-powered microservice architectures. Who is this book for: Software architects and engineers, AI and machine learning professionals, and DevOps engineers
A Practical Guide To Generative Ai Using Amazon Bedrock
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Author : Avik Bhattacharjee
language : en
Publisher: Springer Nature
Release Date : 2025-07-08
A Practical Guide To Generative Ai Using Amazon Bedrock written by Avik Bhattacharjee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-08 with Computers categories.
This comprehensive guide gives you the knowledge and skills you need to excel in Generative AI. From understanding the fundamentals to mastering techniques, this book offers a step-by-step approach to leverage Amazon Bedrock to build, deploy, and secure Generative AI applications. The book presents structured chapters and practical examples to delve into key concepts such as prompt engineering, retrieval-augmented generation, and model evaluation. You will gain profound insights into the Amazon Bedrock platform. The book covers setup, life cycle management, and integration with Amazon SageMaker. The book emphasizes real-world applications, and provides use cases and best practices across industries on topics such as text summarization, image generation, and conversational AI bots. The book tackles vital topics including data privacy, security, responsible AI practices, and guidance on navigating governance and monitoring challenges while ensuring adherence to ethical standards and regulations. The book provides the tools and knowledge needed to excel in the rapidly evolving field of Generative AI. Whether you're a data scientist, AI engineer, or business professional, this book will empower you to harness the full potential of Generative AI and drive innovation in your organization. What You Will Learn Understand the fundamentals of Generative AI and Amazon Bedrock Build Responsible Generative AI applications leveraging Amazon Bedrock Know techniques and best practices See real-world applications Integrate and manage platforms Handle securty and governance issues Evaluate and optimze models Gain future-ready insights Understand the project life cycle when building Generative AI Applications Who This Book Is For Data scientistys, AI/ML engineers and architects, software developers plus AI enthusiasts and studenta and educators, and leaders who want to evangelize within organizatios