Design, build, and secure scalable machine learning (ML) systems to solve real-world business problems with Python and AWS Purchase of the print or Kindle book includes a free PDF eBook Key Features Go in-depth into the ML lifecycle, from ideation and data management to deployment and scaling Apply risk management techniques in the ML lifecycle and design architectural patterns for various ML platforms and solutions Understand the generative AI lifecycle, its core technologies, and implementation risks Book DescriptionDavid Ping, Head of GenAI and ML Solution Architecture for global industries at AWS, provides expert insights and practical examples to help you become a proficient ML solutions architect, linking technical architecture to business-related skills. You'll learn about ML algorithms, cloud infrastructure, system design, MLOps , and how to apply ML to solve real-world business problems. David explains the generative AI project lifecycle and examines Retrieval Augmented Generation (RAG), an effective architecture pattern for generative AI applications. You’ll also learn about open-source technologies, such as Kubernetes/Kubeflow, for building a data science environment and ML pipelines before building an enterprise ML architecture using AWS. As well as ML risk management and the different stages of AI/ML adoption, the biggest new addition to the handbook is the deep exploration of generative AI. By the end of this book , you’ll have gained a comprehensive understanding of AI/ML across all key aspects, including business use cases, data science, real-world solution architecture, risk management, and governance. You’ll possess the skills to design and construct ML solutions that effectively cater to common use cases and follow established ML architecture patterns, enabling you to excel as a true professional in the field.What you will learn Apply ML methodologies to solve business problems across industries Design a practical enterprise ML platform architecture Gain an understanding of AI risk management frameworks and techniques Build an end-to-end data management architecture using AWS Train large-scale ML models and optimize model inference latency Create a business application using artificial intelligence services and custom models Dive into generative AI with use cases, architecture patterns, and RAG Who this book is for This book is for solutions architects working on ML projects, ML engineers transitioning to ML solution architect roles, and MLOps engineers. Additionally, data scientists and analysts who want to enhance their practical knowledge of ML systems engineering, as well as AI/ML product managers and risk officers who want to gain an understanding of ML solutions and AI risk management, will also find this book useful. A basic knowledge of Python, AWS, linear algebra, probability, and cloud infrastructure is required before you get started with this handbook.

Improve your product knowledge and ownership while building secure and scalable machine learning platformsPurchase of the print or Kindle book includes a free PDF eBook.Key FeaturesSolve large-scale machine learning challenges in the cloud with a variety of open-source and AWS tools and frameworksApply risk management techniques in the machine learning lifecycleUnderstand the key challenges and risks around implementing generative AI and learn architecture patterns for some solutionsBook DescriptionDavid Ping, Head of ML Solutions Architecture at AWS, provides valuable insights and practical examples for becoming a highly skilled ML solutions architect, linking technical architecture to business-related skills.You'll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will focus on carefully selected and updated topics like ML algorithms, including a newly added section on generative AI and large language models. You ll also learn about open-source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines before moving on to building an enterprise ML architecture using Amazon Web Services (AWS).In this latest edition, David has updated the entire book to incorporate the latest advancements in science, technology, and solution patterns. The biggest new addition to the handbook is a comprehensive exploration of ML risk management, generative AI, and a deep understanding of the different stages of AI/ML adoption, allowing you to assess your company's position on its AI/ML journeyBy the end of this book, you will have gained a comprehensive understanding of AI/ML across all key aspects, including business use cases, data science, technology, real-world solutions architecture, risk management, governance, and the overall AI/ML journey. Moreover, you will possess the skills to design and construct ML solutions and platforms that effectively cater to common use cases and follow established architecture patterns, enabling you to excel as a true professional in the field.What you will learnApply ML methodologies to solve business problemsDesign a practical enterprise ML platform architectureGain a deep understanding of AI risk management frameworks and techniquesBuild an end-to-end data management architecture using AWSTrain large-scale ML models and optimize model inference latencyCreate a business application using AI services and custom modelsDive into generative AI with use cases, architecture patterns, risks, and ethical considerationsWho this book is forThis book is for data scientists, data engineers, cloud architects, and machine learning enthusiasts who want to become machine learning solutions architects. Also, this book is a great companion for AI/ML product managers and risk officers who want to gain an understanding of ML solutions and AI risk management and AI/ML solutions architects who want to expand their scope of knowledge around AI/ML. You'll need basic knowledge of the Python programming language, AWS, linear algebra, probability, and networking concepts before you get started with this handbook.

Third edition out now with coverage on Generative AI, clean architecture, edge computing, and more Key Features Turn business needs into end-to-end technical architectures with this practical guide Assess and overcome various challenges while updating or modernizing legacy applications Future-proof your architecture with IoT, machine learning, and quantum computing Book DescriptionBecoming a solutions architect requires a hands-on approach, and this edition of the Solutions Architect's Handbook brings exactly that. This handbook will teach you how to create robust, scalable, and fault-tolerant solutions and next-generation architecture designs in a cloud environment. It will also help you build effective product strategies for your business and implement them from start to finish. This new edition features additional chapters on disruptive technologies, such as Internet of Things (IoT), quantum computing, data engineering, and machine learning. It also includes updated discussions on cloud-native architecture, blockchain data storage, and mainframe modernization with public cloud. The Solutions Architect's Handbook provides an understanding of solution architecture and how it fits into an agile enterprise environment. It will take you through the journey of solution architecture design by providing detailed knowledge of design pillars, advanced design patterns, anti-patterns, and the cloud-native aspects of modern software design. By the end of this handbook, you'll have learned the techniques needed to create efficient architecture designs that meet your business requirements.What you will learn Explore the various roles of a solutions architect in the enterprise landscape Implement key design principles and patterns to build high-performance cost-effective solutions Choose the best strategies to secure your architectures and increase their availability Modernize legacy applications with the help of cloud integration Understand how big data processing, machine learning, and IoT fit into modern architecture Integrate a DevOps mindset to promote collaboration, increase operational efficiency, and streamline production Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders who already work in the IT industry and aspire to become solutions architect professionals. Existing solutions architects who want to expand their skillset or get a better understanding of new technologies will also learn valuable new skills. To get started, you'll need a good understanding of the real-world software development process and general programming experience in any language.

From fundamentals and design patterns to the different strategies for creating secure and reliable architectures in AWS cloud, learn everything you need to become a successful solutions architect Key Features Create solutions and transform business requirements into technical architecture with this practical guide Understand various challenges that you might come across while refactoring or modernizing legacy applications Delve into security automation, DevOps, and validation of solution architecture Book DescriptionBecoming a solutions architect gives you the flexibility to work with cutting-edge technologies and define product strategies. This handbook takes you through the essential concepts, design principles and patterns, architectural considerations, and all the latest technology that you need to know to become a successful solutions architect. This book starts with a quick introduction to the fundamentals of solution architecture design principles and attributes that will assist you in understanding how solution architecture benefits software projects across enterprises. You'll learn what a cloud migration and application modernization framework looks like, and will use microservices, event-driven, cache-based, and serverless patterns to design robust architectures. You'll then explore the main pillars of architecture design, including performance, scalability, cost optimization, security, operational excellence, and DevOps. Additionally, you'll also learn advanced concepts relating to big data, machine learning, and the Internet of Things (IoT). Finally, you'll get to grips with the documentation of architecture design and the soft skills that are necessary to become a better solutions architect. By the end of this book, you'll have learned techniques to create an efficient architecture design that meets your business requirements.What you will learn Explore the various roles of a solutions architect and their involvement in the enterprise landscape Approach big data processing, machine learning, and IoT from an architect s perspective and understand how they fit into modern architecture Discover different solution architecture patterns such as event-driven and microservice patterns Find ways to keep yourself updated with new technologies and enhance your skills Modernize legacy applications with the help of cloud integration Get to grips with choosing an appropriate strategy to reduce cost Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders working in the information technology industry who aspire to become solutions architect professionals. A good understanding of the software development process and general programming experience with any language will be useful.

This up-to-date study guide offers 100% coverage of every objective for the current version of the AWS Certified Solutions Architect Professional exam Get complete coverage of all objectives included on the SAA-C02 exam from this comprehensive resource. Written by an expert AWS Solutions Architect and well-respected author, this authoritative guide fully addresses the knowledge and skills required for passing the AWS Certified Solutions Architect – Associate exam. You’ll find learning objectives at the beginning of each chapter, exam tips, practice exam questions, and in-depth explanations. You’ll also build your practical knowledge with the many hands-on labs found throughout this guide. Designed to help you pass the exam with ease, this definitive volume also serves as an essential on-the-job reference. Covers all exam domains, including: Design Resilient Architectures Design High-Performing Architectures Design Secure Applications and Architectures Design Cost-Optimized Architectures Online content includes: 130 practice exam questions Test engine that provides practice exams or quizzes that can be customized by chapter or exam objective

Architects must be proficient in a variety of business practices to contribute to, manage, or launch a successful firm. They are responsible for the same kind of legal, financial, marketing, management, and administrative activities as any other professional. Within these broad categories, however, there are many details, including professional standards and documents, that are unique to the profession of architecture.

From fundamentals and design patterns to the different strategies for creating secure and reliable architectures in AWS cloud, learn everything you need to become a successful solutions architectKey Features* Transform business requirements into end-to-end technical architectures with this practical guide* Assess and overcome the various challenges while updating or modernizing legacy applications* Learn how to future-proof your architecture with IoT, machine learning, and quantum computingBook DescriptionSolutions Architect's Handbook, Second Edition, takes a hands-on approach to helping you become a solutions architect. You will learn how to create robust, scalable, and fault-tolerant solutions and next-generation architecture designs in a cloud environment. This will help you build effective product strategies for your business and implement them from start to finish.The new edition incorporates new chapters on disruptive technologies, such Internet of Things (IoT), quantum computing, data engineering, and machine learning. It also includes updated discussions on cloud-native architecture, blockchain data storage, and mainframe modernization with public cloud.This book provides an understanding of solution architecture and how it fits into an agile enterprise environment. It will take you through the journey of solution architecture design by providing detailed knowledge of design pillars, advanced design patterns, anti-patterns, and the cloud-native aspects of modern software design.By the end of this book, you'll have learned techniques that enable you to create efficient architecture designs that meet your business requirements.What you will learn* Explore the various roles of a solutions architect in the enterprise landscape* Implement key design principles and patterns to build high-performance, cost-effective solutions* Choose appropriate strategies to secure your architectures and increase their availability* Modernize legacy applications with the help of cloud integration* Understand big data processing, machine learning, IoT, and quantum computing, and how they fit into modern architecture* Integrate a DevOps mindset to promote collaboration, increase operational efficiency, and streamline productionWho this book is forThis book is for software developers, system engineers, DevOps engineers, architects, and team leaders working in the information technology industry who aspire to become solutions architect professionals. It will also be useful for existing solutions architects who want to broaden their skillset and learn about new technologies.A good understanding of the real-world software development process and general programming experience with any language will be useful.