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Generative Ai With Amazon Bedrock

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Author : Shikhar Kwatra
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-31

Generative Ai With Amazon Bedrock written by Shikhar Kwatra 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 2024-07-31 with Computers categories.

Become proficient in Amazon Bedrock by taking a hands-on approach to building and scaling generative AI solutions that are robust, secure, and compliant with ethical standards Key Features Learn the foundations of Amazon Bedrock from experienced AWS Machine Learning Specialist Architects Master the core techniques to develop and deploy several AI applications at scale Go beyond writing good prompting techniques and secure scalable frameworks by using advanced tips and tricks Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe concept of generative artificial intelligence has garnered widespread interest, with industries looking to leverage it to innovate and solve business problems. Amazon Bedrock, along with LangChain, simplifies the building and scaling of generative AI applications without needing to manage the infrastructure. Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. You’ll explore techniques such as prompt engineering, retrieval augmentation, fine-tuning generative models, and orchestrating tasks using agents. The chapters take you through real-world scenarios and use cases such as text generation and summarization, image and code generation, and the creation of virtual assistants. The latter part of the book shows you how to effectively monitor and ensure security and privacy in Amazon Bedrock. By the end of this book, you’ll have gained a solid understanding of building and scaling generative AI apps using Amazon Bedrock, along with various architecture patterns and security best practices that will help you solve business problems and drive innovation in your organization.What you will learn Explore the generative AI landscape and foundation models in Amazon Bedrock Fine-tune generative models to improve their performance Explore several architecture patterns for different business use cases Gain insights into ethical AI practices, model governance, and risk mitigation strategies Enhance your skills in employing agents to develop intelligence and orchestrate tasks Monitor and understand metrics and Amazon Bedrock model response Explore various industrial use cases and architectures to solve real-world business problems using RAG Stay on top of architectural best practices and industry standards Who this book is for This book is for generalist application engineers, solution engineers and architects, technical managers, ML advocates, data engineers, and data scientists looking to either innovate within their organization or solve business use cases using generative AI. A basic understanding of AWS APIs and core AWS services for machine learning is expected.

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

Generative Ai With Amazon Bedrock

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Author : Shikhar Kwatra
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-31

Generative Ai With Sap And Amazon Bedrock

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Author : Miguel Figueiredo
language : en
Publisher: Springer Nature
Release Date : 2025-02-19

Generative Ai With Sap And Amazon Bedrock written by Miguel Figueiredo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-19 with Mathematics categories.

Explore Generative AI and understand its key concepts, architecture, and tangible business use cases. This book will help you develop the skills needed to use SAP AI Core service features available in the SAP Business Technology Platform. You’ll examine large language model (LLM) concepts and gain the practical knowledge to unleash the best use of Gen AI. As you progress, you’ll learn how to get started with your own LLM models and work with Generative AI use cases. Additionally, you’ll see how to take advantage Amazon Bedrock stack using AWS SDK for ABAP. To fully leverage your knowledge, Generative AI with SAP and Amazon Bedrock offers practical step-by-step instructions for how to establish a cloud SAP BTP account model and create your first GenAIartifacts. This work is an important prerequisite for those who want to take full advantage of generative AI with SAP. What You Will Learn Master the concepts and terminology of artificial intelligence and GenAI Understand opportunities and impacts for different industries with GenAI Become familiar with SAP AI Core, Amazon Bedrock, AWS SDK for ABAP and develop your firsts GenAI projects Accelerate your development skills Gain more productivity and time implementing GenAI use cases Who this Book Is For Anyone who wants to learn about Generative AI for Enterprise and SAP practitioners who want to take advantage of AI within the SAP ecosystem to support their systems and workflows.

Data Engineering With Aws

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Author : Gareth Eagar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-10-31

Data Engineering With Aws written by Gareth Eagar 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 2023-10-31 with Computers categories.

Looking to revolutionize your data transformation game with AWS? Look no further! From strong foundations to hands-on building of data engineering pipelines, our expert-led manual has got you covered. Key Features Delve into robust AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines Stay up to date with a comprehensive revised chapter on Data Governance Build modern data platforms with a new section covering transactional data lakes and data mesh Book DescriptionThis book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers; implementing a data mesh approach, open-table formats (such as Apache Iceberg), and using DataOps for automation and observability. You'll begin by reviewing the key concepts and essential AWS tools in a data engineer's toolkit and getting acquainted with modern data management approaches. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how that transformed data is used by various data consumers. You’ll learn how to ensure strong data governance, and about populating data marts and data warehouses along with how a data lakehouse fits into the picture. After that, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. Then, you'll explore how the power of machine learning and artificial intelligence can be used to draw new insights from data. In the final chapters, you'll discover transactional data lakes, data meshes, and how to build a cutting-edge data platform on AWS. By the end of this AWS book, you'll be able to execute data engineering tasks and implement a data pipeline on AWS like a pro!What you will learn Seamlessly ingest streaming data with Amazon Kinesis Data Firehose Optimize, denormalize, and join datasets with AWS Glue Studio Use Amazon S3 events to trigger a Lambda process to transform a file Load data into a Redshift data warehouse and run queries with ease Visualize and explore data using Amazon QuickSight Extract sentiment data from a dataset using Amazon Comprehend Build transactional data lakes using Apache Iceberg with Amazon Athena Learn how a data mesh approach can be implemented on AWS Who this book is forThis book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts, while gaining practical experience with common data engineering services on AWS, will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book, but it’s not a prerequisite. Familiarity with the AWS console and core services will also help you follow along.

Advanced Data Analytics With Aws

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Author : Joseph Conley
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-04-17

Advanced Data Analytics With Aws written by Joseph Conley and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-17 with Computers categories.

Master the Fundamentals of Data Analytics at Scale KEY FEATURES ● Comprehensive guide to constructing data engineering workflows spanning diverse data sources ● Expert techniques for transforming and visualizing data to extract actionable insights ● Advanced methodologies for analyzing data and employing machine learning to uncover intricate patterns DESCRIPTION Embark on a transformative journey into the realm of data analytics with AWS with this practical and incisive handbook. Begin your exploration with an insightful introduction to the fundamentals of data analytics, setting the stage for your AWS adventure. The book then covers collecting data efficiently and effectively on AWS, laying the groundwork for insightful analysis. It will dive deep into processing data, uncovering invaluable techniques to harness the full potential of your datasets. The book will equip you with advanced data analysis skills, unlocking the ability to discern complex patterns and insights. It covers additional use cases for data analysis on AWS, from predictive modeling to sentiment analysis, expanding your analytical horizons. The final section of the book will utilize the power of data virtualization and interaction, revolutionizing the way you engage with and derive value from your data. Gain valuable insights into emerging trends and technologies shaping the future of data analytics, and conclude your journey with actionable next steps, empowering you to continue your data analytics odyssey with confidence. WHAT WILL YOU LEARN ● Construct streamlined data engineering workflows capable of ingesting data from diverse sources and formats. ● Employ data transformation tools to efficiently cleanse and reshape data, priming it for analysis. ● Perform ad-hoc queries for preliminary data exploration, uncovering initial insights. ● Utilize prepared datasets to craft compelling, interactive data visualizations that communicate actionable insights. ● Develop advanced machine learning and Generative AI workflows to delve into intricate aspects of complex datasets, uncovering deeper insights. WHO IS THIS BOOK FOR? This book is ideal for aspiring data engineers, analysts, and data scientists seeking to deepen their understanding and practical skills in data engineering, data transformation, visualization, and advanced analytics. It is also beneficial for professionals and students looking to leverage AWS services for their data-related tasks. TABLE OF CONTENTS 1. Introduction to Data Analytics and AWS 2. Getting Started with AWS 3. Collecting Data with AWS 4. Processing Data on AWS 5. Descriptive Analytics on AWS 6. Advanced Data Analysis on AWS 7. Additional Use Cases for Data Analysis 8. Data Visualization and Interaction on AWS 9. The Future of Data Analytics 10. Conclusion and Next Steps Index

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

The Definitive Guide To Machine Learning Operations In Aws

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Author : Neel Sendas
language : en
Publisher: Springer Nature
Release Date : 2025-01-03

The Definitive Guide To Machine Learning Operations In Aws written by Neel Sendas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.

Foreword by Dr. Shreyas Subramanian, Principal Data Scientist, Amazon This book focuses on deploying, testing, monitoring, and automating ML systems in production. It covers AWS MLOps tools like Amazon SageMaker, Data Wrangler, and AWS Feature Store, along with best practices for operating ML systems on AWS. This book explains how to design, develop, and deploy ML workloads at scale using AWS cloud's well-architected pillars. It starts with an introduction to AWS services and MLOps tools, setting up the MLOps environment. It covers operational excellence, including CI/CD pipelines and Infrastructure as code. Security in MLOps, data privacy, IAM, and reliability with automated testing are discussed. Performance efficiency and cost optimization, like Right-sizing ML resources, are explored. The book concludes with MLOps best practices, MLOPS for GenAI, emerging trends, and future developments in MLOps By the end, readers will learn operating ML workloads on the AWS cloud. This book suits software developers, ML engineers, DevOps engineers, architects, and team leaders aspiring to be MLOps professionals on AWS. What you will learn: ● Create repeatable training workflows to accelerate model development ● Catalog ML artifacts centrally for model reproducibility and governance ● Integrate ML workflows with CI/CD pipelines for faster time to production ● Continuously monitor data and models in production to maintain quality ● Optimize model deployment for performance and cost Who this book is for: This book suits ML engineers, DevOps engineers, software developers, architects, and team leaders aspiring to be MLOps professionals on AWS.

Navigating The Ai Frontier Understanding The Benefits And Challenges Of Artificial Intelligence Across Industries

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Author : Dr. Arun B Prasad
language : en
Publisher: Xoffencerpublication
Release Date : 2023-08-21

Navigating The Ai Frontier Understanding The Benefits And Challenges Of Artificial Intelligence Across Industries written by Dr. Arun B Prasad and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-21 with Transportation categories.

The consistent development of information technology (IT) paves the way for companies to make the shift to digital work as their principal mode of operation. This is made feasible by the rapid progress of IT. As a consequence of this, employers are putting pressure on employees to adapt to new forms of employment, which may include less interaction with other people but more interaction with information technology. However, as a consequence of these new ways of doing things, workers won't be able to carry out their responsibilities with the same principles and beliefs that they have been used to bringing to the table in the past. The continual upheaval that takes place in the workplace has the potential to influence the self-beliefs that constitute a person's professional identity at work, also known as the perception of one's function in the workplace. This is because self beliefs are sensitive to being influenced by the perception of one's function in the workplace. The act of having one's identity questioned by an experience that is in direct opposition to who they are may result in a decline in one's sense of self-worth as well as a potential threat to the integrity of one's identity. As a consequence of this, it is possible that activities that are targeted at maintaining self-esteem connected with identity will be necessary in light of the fact that the landscape and experiences of a number of professions have been transformed as a result of the development of technology. The digitization of workplaces is directly responsible for the growing popularity of digital labour as the normal operating procedure in organisations. One of the primary factors that is driving this discussion is the continuing development of artificial intelligence (AI), which can be defined as "the ability of a machine to perform cognitive functions that we associate with human minds, such as perceiving, reasoning, learning, interacting with the environment, problem-solving, decision-making, and even demonstrating creativity." Artificial intelligence is put to use in many different capacities within the field of digital labour, including (managerial) decision making, data analysis and prediction work, or (human-AI) interaction. 1 | P a ge Because of this, artificial intelligence will continually bring about changes to working environments and professions, perhaps putting the lives of people whose jobs are replaced by computers in jeopardy. On the other hand, this might lead to a reduction in value if the people who utilise AI systems have major variances in their perspectives. In addition, the use of AI has the potential to contribute to the growth of ambiguity and the invasion of individuals' right to personal privacy. The phrase "dark side of AI" is often used to refer to this undesirable phenomenon, which outlines the ways in which AI offers risks for individuals, businesses, and society as a whole. However, the adoption of AI in enterprises may not only eliminate or modify current jobs but also create new sectors of labour, such as in the disciplines of engineering, programming, or even social domains. This is because AI may be able to perform some or all of the tasks associated with these vocations. This is due to the fact that AI is capable of learning new things and adjusting to its surroundings. There is an ongoing sense of optimism over artificial intelligence and the economic effects that it will have (Selz, 2020). The public discourse about artificial intelligence has been more optimistic over the last several years; despite this, the concern that AI would displace current jobs continues to outweigh the potential for human and AI collaboration in the future. The interaction between humans and artificial intelligence demonstrates that people's views of AI are based on a wide variety of features to varying degrees. For example, salient signals, affordances, or collaborative interaction may have an effect on a person's emotions and, as a consequence, their intents about artificial intelligence (Shin, 2021). The manner in which an employee applies technology in the course of their work contributes to the formation of that employee's sense of self identity. In order to investigate this matter in a way that is adequate, we are going to adopt the perspective of Carter and who define the word "IT identity" as "the extent to which a person views use of an IT as integral to his or her sense of self." This will allow us to investigate this matter in a manner that is adequate. It is possible that the implementation of AI in the workplace will run opposite to the employees' identification with their activities, which may cause them to engage in resistive behaviours such as an aversion to algorithms on their part. The phenomenon known as "algorithm aversion" is characterised by the fact that employees, when faced with the same conditions as before, prefer to get assistance from a human being rather than from a computer programme. A possible definition of IT identity danger is "the anticipation of harm to an individual's self-beliefs, caused 2 | P a ge by the use of an IT, and the entity it applies to is the individual user of an IT." The individual user of an IT is the entity to whom this definition applies.A term that might be used to describe this obstruction is "IT identity threat." As a consequence of this, having an awareness of the development of upcoming predictors that impact AI resistance based on IT identity risks is very necessary. This is owing to the fact that it is anticipated that the introduction of AI would modify employment inside enterprises, which in turn may have an influence on the identities of the individuals working in such firms.

Genai On Aws

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Author : Olivier Bergeret
language : en
Publisher: John Wiley & Sons
Release Date : 2025-03-19

Genai On Aws written by Olivier Bergeret and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-19 with Computers categories.

The definitive guide to leveraging AWS for generative AI GenAI on AWS: A Practical Approach to Building Generative AI Applications on AWS is an essential guide for anyone looking to dive into the world of generative AI with the power of Amazon Web Services (AWS). Crafted by a team of experienced cloud and software engineers, this book offers a direct path to developing innovative AI applications. It lays down a hands-on roadmap filled with actionable strategies, enabling you to write secure, efficient, and reliable generative AI applications utilizing the latest AI capabilities on AWS. This comprehensive guide starts with the basics, making it accessible to both novices and seasoned professionals. You'll explore the history of artificial intelligence, understand the fundamentals of machine learning, and get acquainted with deep learning concepts. It also demonstrates how to harness AWS's extensive suite of generative AI tools effectively. Through practical examples and detailed explanations, the book empowers you to bring your generative AI projects to life on the AWS platform. In the book, you'll: Gain invaluable insights from practicing cloud and software engineers on developing cutting-edge generative AI applications using AWS Discover beginner-friendly introductions to AI and machine learning, coupled with advanced techniques for leveraging AWS's AI tools Learn from a resource that's ideal for a broad audience, from technical professionals like cloud engineers and software developers to non-technical business leaders looking to innovate with AI Whether you're a cloud engineer, software developer, business leader, or simply an AI enthusiast, Gen AI on AWS is your gateway to mastering generative AI development on AWS. Seize this opportunity for an enduring competitive advantage in the rapidly evolving field of AI. Embark on your journey to building practical, impactful AI applications by grabbing a copy today.

Using Amazon Bedrock

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