Mastering Serverless Agentic Ai
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Mastering Serverless Agentic Ai
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Author : BRIAN. PITMAN
language : en
Publisher: Independently Published
Release Date : 2025-02-21
Mastering Serverless Agentic Ai written by BRIAN. PITMAN and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-21 with Computers categories.
Mastering Serverless Agentic AI: Build Scalable, Autonomous AI Agents-Optimize Workflows, Automate Decisions, and Seamlessly Integrate with Cloud Services Using Serverless Architecture Unlock the future of AI with Mastering Serverless Agentic AI, the ultimate guide to building intelligent, autonomous systems that scale effortlessly in the cloud. This groundbreaking book provides a comprehensive, hands-on approach to designing, deploying, and managing serverless AI agents capable of reasoning, decision-making, and real-world interaction using cutting-edge technologies like Amazon Bedrock, Retrieval-Augmented Generation (RAG), LangChain, AWS API Gateway, and OpenSearch. Whether you're an AI engineer, cloud architect, or enterprise innovator, this book equips you with actionable strategies to develop context-aware, multimodal, and self-directed AI agents that seamlessly integrate with APIs, databases, and external tools. You'll explore advanced Agentic AI architectures, leverage multi-agent systems, and implement secure, scalable AI pipelines using best practices in serverless computing and modern cloud frameworks. Key topics include: Building AI-driven chatbots, virtual assistants, and decision-making agents Implementing advanced memory systems with vector databases and contextual retrieval Connecting AI agents to APIs for real-world automation and business intelligence Harnessing AWS Bedrock, OpenSearch, and API Gateway for enterprise-grade AI applications Optimizing RAG-based architectures for next-generation AI-powered workflows Securing AI agents with IAM policies, responsible AI practices, and compliance frameworks Scaling AI agents across cloud and edge computing for maximum efficiency With step-by-step tutorials, real-world use cases, and expert insights, this book serves as your practical roadmap to mastering autonomous AI systems in production environments. If you're ready to future-proof your AI skills and stay ahead of the next wave of AI innovation, Mastering Serverless Agentic AI is your essential resource.
Serverless Agentic Workflows With Amazon Bedrock
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Author : BRIAN. PITMAN
language : en
Publisher: Independently Published
Release Date : 2025-02-19
Serverless Agentic Workflows With Amazon Bedrock written by BRIAN. PITMAN and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-19 with Computers categories.
Serverless Agentic Workflows with Amazon Bedrock: Mastering Agentic AI for Building Self-Directed, Scalable Systems with Integrated Tools, Code Execution, and Responsible Guardrails is your definitive guide to the next generation of intelligent systems. This book unites the power of Amazon Bedrock generative AI and cutting-edge serverless architectures to create context-aware, multimodal applications that are designed to work autonomously in real-world environments. Inside, you will explore how to master generative AI applications, build self-directed AI systems, and design modern agentic architectures that leverage Retrieval-Augmented Generation (RAG) for dynamic, intelligent decision-making. From practical, step-by-step instructions in Python to deep dives into cognitive frameworks for agentic AI, this book offers comprehensive insights into building multi-agent systems that are not only scalable and efficient but also ethically responsible. Learn to integrate external tools, connect seamlessly with CRMs and support repositories, and orchestrate multiple agent actions to create truly autonomous AI systems. Whether you are focused on building innovative, context-aware applications on AWS, mastering agentic RAG architectures, or preparing for the artificial intelligence revolution, this book provides the practical, hands-on approach you need. Designed for engineers, architects, and business leaders, this practical guide to innovation in AI equips you with the skills to future-proof your organization. By blending detailed code illustrations with robust architectural insights, it shows you how to create intelligent systems that meet real-world demands while adhering to best practices for responsible deployment. Transform your approach to AI with a resource that is as forward-thinking as it is practical. Embrace the future of autonomous, agentic AI systems and revolutionize your organization with strategies that drive efficiency, innovation, and lasting success.
Building Scalable Autonomous Ai Systems With Amazon Bedrock
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Author : RONALD. TAYLOR
language : en
Publisher: Independently Published
Release Date : 2025-02-21
Building Scalable Autonomous Ai Systems With Amazon Bedrock written by RONALD. TAYLOR and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-21 with Computers categories.
Building Scalable, Autonomous AI Systems with Amazon Bedrock is the definitive guide for developers, AI architects, and business leaders looking to harness the power of serverless, agentic AI workflows. This book provides a step-by-step, hands-on approach to building intelligent, context-aware AI applications using Amazon Bedrock, retrieval-augmented generation (RAG), and multi-agent systems. Whether you are optimizing enterprise automation, scaling autonomous AI assistants, or integrating AI with real-world applications, this book delivers actionable insights and production-grade strategies. From mastering agentic AI architecture and secure code execution to implementing bias mitigation, explainability, and compliance guardrails, this book covers everything needed to design and deploy powerful AI-driven solutions. Learn how to leverage AWS Lambda, EventBridge, and serverless computing for cost-efficient, high-performance AI applications while ensuring security, reliability, and ethical AI governance. Key topics include: ✔ Agentic AI Systems with RAG - How AI agents retrieve, reason, and act autonomously ✔ Building Scalable, Cost-Optimized AI Pipelines - Real-world use cases in finance, healthcare, and customer support ✔ Multi-Agent Architectures and Cognitive AI Frameworks - Developing self-directed, multimodal AI ✔ AI and Emerging Technologies - Integrating blockchain, IoT, and quantum computing for next-gen AI systems Perfect for AI engineers, AWS developers, and tech innovators, this book offers cutting-edge techniques to future-proof your AI applications in an era of autonomous, scalable, and responsible AI.
Building Scalable Autonomous Ai Systems With Amazon Bedrock
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Author : RONALD. TAYLOR
language : en
Publisher:
Release Date : 2025
Building Scalable Autonomous Ai Systems With Amazon Bedrock written by RONALD. TAYLOR and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
Serverless Agentic Ai
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Author : Ronald Taylor
language : en
Publisher: Independently Published
Release Date : 2025-02-27
Serverless Agentic Ai written by Ronald Taylor and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Computers categories.
Serverless Agentic AI: Build Autonomous AI Agents Using Serverless Technology for Scalable Automation and Seamless Cloud Integration Unlock the future of AI automation with Serverless Agentic AI, the definitive guide to building intelligent, self-directed AI agents using serverless computing. Whether you're an AI engineer, cloud architect, or technology leader, this book provides the knowledge and tools to design scalable, efficient, and cost-effective AI systems that operate autonomously-without the burden of managing infrastructure. Grounded in cutting-edge research and real-world applications, this book takes you step by step through designing agentic AI systems that leverage retrieval-augmented generation (RAG), multimodal intelligence, and multi-agent collaboration. You'll explore AWS-native solutions, cloud-edge hybrid approaches, and cognitive frameworks to develop AI-driven applications that adapt dynamically to their environments. From AI-powered business automation to real-time decision-making, this book demonstrates how to integrate serverless functions, event-driven architectures, and scalable storage solutions to build highly responsive, context-aware AI agents. Through hands-on insights and practical strategies, you'll master techniques for optimizing performance, securing AI workloads, and ensuring compliance-while keeping operational costs under control. What You'll Learn: Architect autonomous AI agents using serverless computing and modern cloud technologies. Implement retrieval-augmented generation (RAG) to enhance agent decision-making with real-time knowledge. Design multi-agent AI systems that collaborate, learn, and execute complex workflows. Optimize AI execution time, resource allocation, and cost-efficiency in large-scale automation. Deploy context-aware multimodal AI applications that integrate text, vision, and audio intelligence. Secure AI workloads using identity and access management (IAM), encryption, and compliance best practices. Leverage edge computing for low-latency AI inference and hybrid cloud strategies for maximum scalability. With insights from modern AI architectures, AWS-native tools, and practical agentic AI frameworks, Serverless Agentic AI bridges the gap between theory and hands-on implementation. Whether you're building next-generation chatbots, predictive analytics platforms, or fully autonomous AI-driven enterprises, this book equips you with everything you need to design intelligent, self-directed AI systems that operate at scale. Stay ahead of the AI revolution-build, deploy, and master Serverless Agentic AI today.
Data Science For Marketing Analytics
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Author : Mirza Rahim Baig
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-07
Data Science For Marketing Analytics written by Mirza Rahim Baig 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 2021-09-07 with Computers categories.
Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.
Python For Devops
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Author : Noah Gift
language : en
Publisher: O'Reilly Media
Release Date : 2019-12-12
Python For Devops written by Noah Gift and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-12 with Computers categories.
Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project
Cmdb Systems
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Author : Dennis Drogseth
language : en
Publisher: Morgan Kaufmann
Release Date : 2015-03-22
Cmdb Systems written by Dennis Drogseth and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-22 with Computers categories.
CMDB Systems: Making Change Work in the Age of Cloud and Agile shows you how an integrated database across all areas of an organization's information system can help make organizations more efficient reduce challenges during change management and reduce total cost of ownership (TCO). In addition, this valuable reference provides guidelines that will enable you to avoid the pitfalls that cause CMDB projects to fail and actually shorten the time required to achieve an implementation of a CMDB. Drawing upon extensive experience and using illustrative real world examples, Rick Sturm, Dennis Drogseth and Dan Twing discuss: - Unique insights from extensive industry exposure, research and consulting on the evolution of CMDB/CMS technology and ongoing dialog with the vendor community in terms of current and future CMDB/CMS design and plans - Proven and structured best practices for CMDB deployments - Clear and documented insights into the impacts of cloud computing and other advances on CMDB/CMS futures - Discover unique insights from industry experts who consult on the evolution of CMDB/CMS technology and will show you the steps needed to successfully plan, design and implement CMDB - Covers related use-cases from retail, manufacturing and financial verticals from real-world CMDB deployments - Provides structured best practices for CMDB deployments - Discusses how CMDB adoption can lower total cost of ownership, increase efficiency and optimize the IT enterprise
Pragmatic Ai
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Author : Noah Gift
language : en
Publisher: Addison-Wesley Professional
Release Date : 2018-07-12
Pragmatic Ai written by Noah Gift and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-12 with Computers categories.
Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Practical Mlops
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Author : Noah Gift
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-09-14
Practical Mlops written by Noah Gift and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-14 with Computers categories.
Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start. You'll discover how to: Apply DevOps best practices to machine learning Build production machine learning systems and maintain them Monitor, instrument, load-test, and operationalize machine learning systems Choose the correct MLOps tools for a given machine learning task Run machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware