Download or read book Building AI Applications with Microsoft Semantic Kernel written by Lucas A. Meyer and published by Packt Publishing Ltd. This book was released on 2024-06-21 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the power of GenAI by effortlessly linking your C# and Python apps with cutting-edge models, orchestrating diverse AI services with finesse, and crafting bespoke applications through immersive, real-world examples Key Features Link your C# and Python applications with the latest AI models from OpenAI Combine and orchestrate different AI services such as text and image generators Create your own AI apps with real-world use case examples that show you how to use basic generative AI, create images, process documents, use a vector database Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the fast-paced world of AI, developers are constantly seeking efficient ways to integrate AI capabilities into their apps. Microsoft Semantic Kernel simplifies this process by using the GenAI features from Microsoft and OpenAI. Written by Lucas A. Meyer, a Principal Research Scientist in Microsoft’s AI for Good Lab, this book helps you get hands on with Semantic Kernel. It begins by introducing you to different generative AI services such as GPT-3.5 and GPT-4, demonstrating their integration with Semantic Kernel. You’ll then learn to craft prompt templates for reuse across various AI services and variables. Next, you’ll learn how to add functionality to Semantic Kernel by creating your own plugins. The second part of the book shows you how to combine multiple plugins to execute complex actions, and how to let Semantic Kernel use its own AI to solve complex problems by calling plugins, including the ones made by you. The book concludes by teaching you how to use vector databases to expand the memory of your AI services and how to help AI remember the context of earlier requests. You’ll also be guided through several real-world examples of applications, such as RAG and custom GPT agents. By the end of this book, you'll have gained the knowledge you need to start using Semantic Kernel to add AI capabilities to your applications.What you will learn Write reusable AI prompts and connect to different AI providers Create new plugins that extend the capabilities of AI services Understand how to combine multiple plugins to execute complex actions Orchestrate multiple AI services to accomplish a task Leverage the powerful planner to automatically create appropriate AI calls Use vector databases as additional memory for your AI tasks Deploy your application to ChatGPT, making it available to hundreds of millions of users Who this book is for This book is for beginner-level to experienced .NET or Python software developers who want to quickly incorporate the latest AI technologies into their applications, without having to learn the details of every new AI service. Product managers with some development experience will find this book helpful while creating proof-of-concept applications. This book requires working knowledge of programming basics.

Download or read book Tools and Skills for NET 8 written by Mark J. Price and published by Packt Publishing Ltd. This book was released on 2024-07-30 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elevate your career by mastering key .NET tools and skills, including debugging, source code management, testing, cloud-native development, intelligent apps and more. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Coverage of key .NET tools and skills including refactoring, source code management, debugging, memory troubleshooting, and more Practical guidance on using code editors effectively, implementing best practices, and protecting data Explore cutting-edge techniques like building intelligent apps, cloud native development with .NET Aspire, and Docker containerization Book DescriptionUnlock the full potential of .NET development with Tools and Skills for .NET 8. Dive into source code management using Git and learn how to navigate projects while ensuring version control. Discover advanced debugging techniques and troubleshooting strategies to identify and resolve issues, and gain practical insights on documenting your code, APIs, and services, fostering project clarity and maintainability. Delve into the world of cryptography, ensuring confidentiality and integrity throughout your development lifecycle. Elevate your skills as you explore cutting-edge topics such as building intelligent apps using custom LLM-based chat services, mastering dependency injection, optimizing performance through testing, and Docker containerization. Harness the power of cloud-native development with .NET Aspire, unlocking the benefits of modern cloud platforms. With guidance on software architecture best practices, this book empowers you to build robust, scalable and maintainable applications. Advance your career with invaluable insights on job readiness and interview preparation, positioning yourself as a top-tier candidate in today's competitive job market. Whether you're a seasoned .NET professional or an aspiring developer looking to enhance your skills, this book is your ultimate companion on the journey to .NET mastery.What you will learn Make the most of code editor tools for efficient development Learn advanced debugging techniques and troubleshooting strategies Understand how to protect data and applications using cryptography Build a custom LLM-based chat service Discover how to master dependency injection Optimize performance through benchmarking and testing Delve into cloud-native development using .NET Aspire Advance your career with advice on job readiness and interviews Who this book is for .NET professionals seeking to enhance their expertise, as well as aspiring developers aiming to advance their careers in the field. This book caters to individuals eager to master essential .NET tools, refine their development practices, explore advanced techniques and cutting-edge tools, and prepare themselves for job opportunities and interviews in the competitive landscape of .NET development

Download or read book Azure OpenAI Service for Cloud Native Applications written by Adrián González Sánchez and published by "O'Reilly Media, Inc.". This book was released on 2024-06-27 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service—using powerful generative AI models such as GPT-4 and GPT-4o—within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts. Ideal for software and cloud developers, product managers, architects, and engineers, as well as cloud-enabled data scientists, this book will help you: Learn how to implement cloud native applications with Azure OpenAI Service Deploy, customize, and integrate Azure OpenAI Service with your applications Customize large language models and orchestrate knowledge with company-owned data Use advanced roadmaps to plan your generative AI project Estimate cost and plan generative AI implementations for adopter companies

Download or read book Building AI Intensive Python Applications written by Rachelle Palmer and published by Packt Publishing Ltd. This book was released on 2024-09-06 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master retrieval-augmented generation architecture and fine-tune your AI stack, along with discovering real-world use cases and best practices to create powerful AI apps Key Features Get to grips with the fundamentals of LLMs, vector databases, and Python frameworks Implement effective retrieval-augmented generation strategies with MongoDB Atlas Optimize AI models for performance and accuracy with model compression and deployment optimization Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe era of generative AI is upon us, and this book serves as a roadmap to harness its full potential. With its help, you’ll learn the core components of the AI stack: large language models (LLMs), vector databases, and Python frameworks, and see how these technologies work together to create intelligent applications. The chapters will help you discover best practices for data preparation, model selection, and fine-tuning, and teach you advanced techniques such as retrieval-augmented generation (RAG) to overcome common challenges, such as hallucinations and data leakage. You’ll get a solid understanding of vector databases, implement effective vector search strategies, refine models for accuracy, and optimize performance to achieve impactful results. You’ll also identify and address AI failures to ensure your applications deliver reliable and valuable results. By evaluating and improving the output of LLMs, you’ll be able to enhance their performance and relevance. By the end of this book, you’ll be well-equipped to build sophisticated AI applications that deliver real-world value.What you will learn Understand the architecture and components of the generative AI stack Explore the role of vector databases in enhancing AI applications Master Python frameworks for AI development Implement Vector Search in AI applications Find out how to effectively evaluate LLM output Overcome common failures and challenges in AI development Who this book is for This book is for software engineers and developers looking to build intelligent applications using generative AI. While the book is suitable for beginners, a basic understanding of Python programming is required to make the most of it.

Download or read book Programming Large Language Models with Azure Open AI written by Francesco Esposito and published by Microsoft Press. This book was released on 2024-04-03 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use LLMs to build better business software applications Autonomously communicate with users and optimize business tasks with applications built to make the interaction between humans and computers smooth and natural. Artificial Intelligence expert Francesco Esposito illustrates several scenarios for which a LLM is effective: crafting sophisticated business solutions, shortening the gap between humans and software-equipped machines, and building powerful reasoning engines. Insight into prompting and conversational programming—with specific techniques for patterns and frameworks—unlock how natural language can also lead to a new, advanced approach to coding. Concrete end-to-end demonstrations (featuring Python and ASP.NET Core) showcase versatile patterns of interaction between existing processes, APIs, data, and human input. Artificial Intelligence expert Francesco Esposito helps you: Understand the history of large language models and conversational programming Apply prompting as a new way of coding Learn core prompting techniques and fundamental use-cases Engineer advanced prompts, including connecting LLMs to data and function calling to build reasoning engines Use natural language in code to define workflows and orchestrate existing APIs Master external LLM frameworks Evaluate responsible AI security, privacy, and accuracy concerns Explore the AI regulatory landscape Build and implement a personal assistant Apply a retrieval augmented generation (RAG) pattern to formulate responses based on a knowledge base Construct a conversational user interface For IT Professionals and Consultants For software professionals, architects, lead developers, programmers, and Machine Learning enthusiasts For anyone else interested in natural language processing or real-world applications of human-like language in software

Download or read book Building LLM Powered Applications written by Valentina Alto and published by Packt Publishing Ltd. This book was released on 2024-05-22 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get hands-on with GPT 3.5, GPT 4, LangChain, Llama 2, Falcon LLM and more, to build LLM-powered sophisticated AI applications Key Features Embed LLMs into real-world applications Use LangChain to orchestrate LLMs and their components within applications Grasp basic and advanced techniques of prompt engineering Book DescriptionBuilding LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer, ultimately paving the way for the emergence of large foundation models (LFMs) that extend the boundaries of AI capabilities. The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain, we guide you through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio. Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.What you will learn Explore the core components of LLM architecture, including encoder-decoder blocks and embeddings Understand the unique features of LLMs like GPT-3.5/4, Llama 2, and Falcon LLM Use AI orchestrators like LangChain, with Streamlit for the frontend Get familiar with LLM components such as memory, prompts, and tools Learn how to use non-parametric knowledge and vector databases Understand the implications of LFMs for AI research and industry applications Customize your LLMs with fine tuning Learn about the ethical implications of LLM-powered applications Who this book is for Software engineers and data scientists who want hands-on guidance for applying LLMs to build applications. The book will also appeal to technical leaders, students, and researchers interested in applied LLM topics. We don’t assume previous experience with LLM specifically. But readers should have core ML/software engineering fundamentals to understand and apply the content.

Download or read book Data Science with NET and Polyglot Notebooks written by Matt Eland and published by Packt Publishing Ltd. This book was released on 2024-08-30 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: ProgExpand your skillset by learning how to perform data science, machine learning, and generative AI experiments in .NET Interactive notebooks using a variety of languages, including C#, F#, SQL, and PowerShell Key Features Learn Conduct a full range of data science experiments with clear explanations from start to finish Learn key concepts in data analytics, machine learning, and AI and apply them to solve real-world problems Access all of the code online as a notebook and interactive GitHub Codespace Purchase of the print or Kindle book includes a free PDF eBook Book Description As the fields of data science, machine learning, and artificial intelligence rapidly evolve, .NET developers are eager to leverage their expertise to dive into these exciting domains but are often unsure of how to do so. Data Science in .NET with Polyglot Notebooks is the practical guide you need to seamlessly bring your .NET skills into the world of analytics and AI. With Microsoft’s .NET platform now robustly supporting machine learning and AI tasks, the introduction of tools such as .NET Interactive kernels and Polyglot Notebooks has opened up a world of possibilities for .NET developers. This book empowers you to harness the full potential of these cutting-edge technologies, guiding you through hands-on experiments that illustrate key concepts and principles. Through a series of interactive notebooks, you’ll not only master technical processes but also discover how to integrate these new skills into your current role or pivot to exciting opportunities in the data science field. By the end of the book, you’ll have acquired the necessary knowledge and confidence to apply cutting-edge data science techniques and deliver impactful solutions within the .NET ecosystem. What you will learn Load, analyze, and transform data using DataFrames, data visualization, and descriptive statistics Train machine learning models with ML.NET for classification and regression tasks Customize ML.NET model training pipelines with AutoML, transforms, and model trainers Apply best practices for deploying models and monitoring their performance Connect to generative AI models using Polyglot Notebooks Chain together complex AI tasks with AI orchestration, RAG, and Semantic Kernel Create interactive online documentation with Mermaid charts and GitHub Codespaces Who this book is for This book is for experienced C# or F# developers who want to transition into data science and machine learning while leveraging their .NET expertise. It’s ideal for those looking to learn ML.NET and Semantic kernel and extend their .NET skills to data science, machine learning, and Generative AI Workflows.rammer’s guide to data science using ML.NET, OpenAI, and Semantic Kernel

Download or read book Azure OpenAI Service for Cloud Native Applications written by Adrián González Sánchez and published by "O'Reilly Media, Inc.". This book was released on 2024-06-27 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service—using powerful generative AI models such as GPT-4 and GPT-4o—within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts. Ideal for software and cloud developers, product managers, architects, and engineers, as well as cloud-enabled data scientists, this book will help you: Learn how to implement cloud native applications with Azure OpenAI Service Deploy, customize, and integrate Azure OpenAI Service with your applications Customize large language models and orchestrate knowledge with company-owned data Use advanced roadmaps to plan your generative AI project Estimate cost and plan generative AI implementations for adopter companies

Download or read book Generative AI for Cloud Solutions written by Paul Singh and published by Packt Publishing Ltd. This book was released on 2024-04-22 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore Generative AI, the engine behind ChatGPT, and delve into topics like LLM-infused frameworks, autonomous agents, and responsible innovation, to gain valuable insights into the future of AI Key Features Gain foundational GenAI knowledge and understand how to scale GenAI/ChatGPT in the cloud Understand advanced techniques for customizing LLMs for organizations via fine-tuning, prompt engineering, and responsible AI Peek into the future to explore emerging trends like multimodal AI and autonomous agents Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGenerative artificial intelligence technologies and services, including ChatGPT, are transforming our work, life, and communication landscapes. To thrive in this new era, harnessing the full potential of these technologies is crucial. Generative AI for Cloud Solutions is a comprehensive guide to understanding and using Generative AI within cloud platforms. This book covers the basics of cloud computing and Generative AI/ChatGPT, addressing scaling strategies and security concerns. With its help, you’ll be able to apply responsible AI practices and other methods such as fine-tuning, RAG, autonomous agents, LLMOps, and Assistants APIs. As you progress, you’ll learn how to design and implement secure and scalable ChatGPT solutions on the cloud, while also gaining insights into the foundations of building conversational AI, such as chatbots. This process will help you customize your AI applications to suit your specific requirements. By the end of this book, you’ll have gained a solid understanding of the capabilities of Generative AI and cloud computing, empowering you to develop efficient and ethical AI solutions for a variety of applications and services.What you will learn Get started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function together Understand how we started applying NLP to concepts like transformers Grasp the process of fine-tuning and developing apps based on RAG Explore effective prompt engineering strategies Acquire insights into the app development frameworks and lifecycles of LLMs, including important aspects of LLMOps, autonomous agents, and Assistants APIs Discover how to scale and secure GenAI systems, while understanding the principles of responsible AI Who this book is for This artificial intelligence book is for aspiring cloud architects, data analysts, cloud developers, data scientists, AI researchers, technical business leaders, and technology evangelists looking to understanding the interplay between GenAI and cloud computing. Some chapters provide a broad overview of GenAI, which are suitable for readers with basic to no prior AI experience, aspiring to harness AI's potential. Other chapters delve into technical concepts that require intermediate data and AI skills. A basic understanding of a cloud ecosystem is required to get the most out of this book.

Download or read book Building Data Driven Applications with LlamaIndex written by Andrei Gheorghiu and published by Packt Publishing Ltd. This book was released on 2024-05-10 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve real-world problems easily with artificial intelligence (AI) using the LlamaIndex data framework to enhance your LLM-based Python applications Key Features Examine text chunking effects on RAG workflows and understand security in RAG app development Discover chatbots and agents and learn how to build complex conversation engines Build as you learn by applying the knowledge you gain to a hands-on project Book DescriptionDiscover the immense potential of Generative AI and Large Language Models (LLMs) with this comprehensive guide. Learn to overcome LLM limitations, such as contextual memory constraints, prompt size issues, real-time data gaps, and occasional ‘hallucinations’. Follow practical examples to personalize and launch your LlamaIndex projects, mastering skills in ingesting, indexing, querying, and connecting dynamic knowledge bases. From fundamental LLM concepts to LlamaIndex deployment and customization, this book provides a holistic grasp of LlamaIndex's capabilities and applications. By the end, you'll be able to resolve LLM challenges and build interactive AI-driven applications using best practices in prompt engineering and troubleshooting Generative AI projects.What you will learn Understand the LlamaIndex ecosystem and common use cases Master techniques to ingest and parse data from various sources into LlamaIndex Discover how to create optimized indexes tailored to your use cases Understand how to query LlamaIndex effectively and interpret responses Build an end-to-end interactive web application with LlamaIndex, Python, and Streamlit Customize a LlamaIndex configuration based on your project needs Predict costs and deal with potential privacy issues Deploy LlamaIndex applications that others can use Who this book is for This book is for Python developers with basic knowledge of natural language processing (NLP) and LLMs looking to build interactive LLM applications. Experienced developers and conversational AI developers will also benefit from the advanced techniques covered in the book to fully unleash the capabilities of the framework.

Download or read book Generative AI with LangChain written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2023-12-22 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.

Download or read book C Interview Guide written by Konstantin Semenenko and published by Packt Publishing Ltd. This book was released on 2024-03-08 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Catapult your C# journey with this guide to crafting standout resumes, mastering advanced concepts, and navigating job offers with real-world insights for unparalleled success in programming and interviews Key Features Acquire a strong foundation in syntax, data types, and object-oriented programming to code confidently Develop strategies for addressing behavioral questions, tackle technical challenges, and showcase your coding skills Augment your C# programming skills with valuable insights from industry experts Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIf you're gearing up for technical interviews by enhancing your programming skills and aiming for a successful career in C# programming and software development, the C# Interview Guide is your key to interview success. Designed to equip you with essential skills for excelling in technical interviews, this guide spans a broad spectrum, covering fundamental C# programming concepts to intricate technical details. As you progress, you'll develop proficiency in crafting compelling resumes, adeptly answering behavioral questions, and navigating the complexities of salary negotiations and job evaluations. What sets this book apart is its coverage, extending beyond technical know-how and incorporating real-world experiences and expert insights from industry professionals. This comprehensive approach, coupled with guidance on overcoming challenges, ranging from interview preparation to post-interview strategies, makes this guide an invaluable resource for those aspiring to advance in their C# programming careers. By the end of this guide, you’ll emerge with a solid understanding of C# programming, advanced technical interview skills, and the ability to apply industry best practices.What you will learn Craft compelling resumes and cover letters for impactful job applications Demonstrate proficiency in fundamental C# programming concepts and syntax Master advanced C# topics, including LINQ, asynchronous programming, and design patterns Implement best practices for writing clean, maintainable C# code Use popular C# development tools and frameworks, such as .NET and .NET Core Negotiate salary, evaluate job offers, and build a strong C# portfolio Apply soft skills for successful interactions in C# development roles Who this book is for This book is for individuals aspiring to pursue a career in C# programming or software development. Whether you are a beginner or experienced professional, this guide will enhance your technical interview skills and C# programming knowledge.

Download or read book Pro NET Memory Management written by Konrad Kokosa and published by Apress. This book was released on 2018-11-12 with total page 1091 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand .NET memory management internal workings, pitfalls, and techniques in order to effectively avoid a wide range of performance and scalability problems in your software. Despite automatic memory management in .NET, there are many advantages to be found in understanding how .NET memory works and how you can best write software that interacts with it efficiently and effectively. Pro .NET Memory Management is your comprehensive guide to writing better software by understanding and working with memory management in .NET. Thoroughly vetted by the .NET Team at Microsoft, this book contains 25 valuable troubleshooting scenarios designed to help diagnose challenging memory problems. Readers will also benefit from a multitude of .NET memory management “rules” to live by that introduce methods for writing memory-aware code and the means for avoiding common, destructive pitfalls. What You'll LearnUnderstand the theoretical underpinnings of automatic memory management Take a deep dive into every aspect of .NET memory management, including detailed coverage of garbage collection (GC) implementation, that would otherwise take years of experience to acquire Get practical advice on how this knowledge can be applied in real-world software development Use practical knowledge of tools related to .NET memory management to diagnose various memory-related issuesExplore various aspects of advanced memory management, including use of Span and Memory types Who This Book Is For .NET developers, solution architects, and performance engineers

Download or read book Generative AI and Implications for Ethics Security and Data Management written by Gomathi Sankar, Jeganathan and published by IGI Global. This book was released on 2024-08-21 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people’s data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.

Download or read book Adversarial AI Attacks Mitigations and Defense Strategies written by John Sotiropoulos and published by Packt Publishing Ltd. This book was released on 2024-07-26 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand how adversarial attacks work against predictive and generative AI, and learn how to safeguard AI and LLM projects with practical examples leveraging OWASP, MITRE, and NIST Key Features Understand the connection between AI and security by learning about adversarial AI attacks Discover the latest security challenges in adversarial AI by examining GenAI, deepfakes, and LLMs Implement secure-by-design methods and threat modeling, using standards and MLSecOps to safeguard AI systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAdversarial attacks trick AI systems with malicious data, creating new security risks by exploiting how AI learns. This challenges cybersecurity as it forces us to defend against a whole new kind of threat. This book demystifies adversarial attacks and equips cybersecurity professionals with the skills to secure AI technologies, moving beyond research hype or business-as-usual strategies. The strategy-based book is a comprehensive guide to AI security, presenting a structured approach with practical examples to identify and counter adversarial attacks. This book goes beyond a random selection of threats and consolidates recent research and industry standards, incorporating taxonomies from MITRE, NIST, and OWASP. Next, a dedicated section introduces a secure-by-design AI strategy with threat modeling to demonstrate risk-based defenses and strategies, focusing on integrating MLSecOps and LLMOps into security systems. To gain deeper insights, you’ll cover examples of incorporating CI, MLOps, and security controls, including open-access LLMs and ML SBOMs. Based on the classic NIST pillars, the book provides a blueprint for maturing enterprise AI security, discussing the role of AI security in safety and ethics as part of Trustworthy AI. By the end of this book, you’ll be able to develop, deploy, and secure AI systems effectively.What you will learn Understand poisoning, evasion, and privacy attacks and how to mitigate them Discover how GANs can be used for attacks and deepfakes Explore how LLMs change security, prompt injections, and data exposure Master techniques to poison LLMs with RAG, embeddings, and fine-tuning Explore supply-chain threats and the challenges of open-access LLMs Implement MLSecOps with CIs, MLOps, and SBOMs Who this book is for This book tackles AI security from both angles - offense and defense. AI builders (developers and engineers) will learn how to create secure systems, while cybersecurity professionals, such as security architects, analysts, engineers, ethical hackers, penetration testers, and incident responders will discover methods to combat threats and mitigate risks posed by attackers. The book also provides a secure-by-design approach for leaders to build AI with security in mind. To get the most out of this book, you’ll need a basic understanding of security, ML concepts, and Python.

Download or read book Ultimate Azure Data Scientist Associate DP 100 Certification Guide written by Rajib Kumar De and published by Orange Education Pvt Ltd. This book was released on 2024-06-26 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: TAGLINE Empower Your Data Science Journey: From Exploration to Certification in Azure Machine Learning KEY FEATURES ● Offers deep dives into key areas such as data preparation, model training, and deployment, ensuring you master each concept. ● Covers all exam objectives in detail, ensuring a thorough understanding of each topic required for the DP-100 certification. ● Includes hands-on labs and practical examples to help you apply theoretical knowledge to real-world scenarios, enhancing your learning experience. DESCRIPTION Ultimate Azure Data Scientist Associate (DP-100) Certification Guide is your essential resource for achieving the Microsoft Azure Data Scientist Associate certification. This guide covers all exam objectives, helping you design and prepare machine learning solutions, explore data, train models, and manage deployment and retraining processes. The book starts with the basics and advances through hands-on exercises and real-world projects, to help you gain practical experience with Azure's tools and services. The book features certification-oriented Q&A challenges that mirror the actual exam, with detailed explanations to help you thoroughly grasp each topic. Perfect for aspiring data scientists, IT professionals, and analysts, this comprehensive guide equips you with the expertise to excel in the DP-100 exam and advance your data science career. WHAT WILL YOU LEARN ● Design and prepare effective machine learning solutions in Microsoft Azure. ● Learn to develop complete machine learning training pipelines, with or without code. ● Explore data, train models, and validate ML pipelines efficiently. ● Deploy, manage, and optimize machine learning models in Azure. ● Utilize Azure's suite of data science tools and services, including Prompt Flow, Model Catalog, and AI Studio. ● Apply real-world data science techniques to business problems. ● Confidently tackle DP-100 certification exam questions and scenarios. WHO IS THIS BOOK FOR? This book is for aspiring Data Scientists, IT Professionals, Developers, Data Analysts, Students, and Business Professionals aiming to Master Azure Data Science. Prior knowledge of basic Data Science concepts and programming, particularly in Python, will be beneficial for making the most of this comprehensive guide. TABLE OF CONTENTS 1. Introduction to Data Science and Azure 2. Setting Up Your Azure Environment 3. Data Ingestion and Storage in Azure 4. Data Transformation and Cleaning 5. Introduction to Machine Learning 6. Azure Machine Learning Studio 7. Model Deployment and Monitoring 8. Embracing AI Revolution Azure 9. Responsible AI and Ethics 10. Big Data Analytics with Azure 11. Real-World Applications and Case Studies 12. Conclusion and Next Steps Index

Download or read book John Maeda Designing the Future written by Interviews and and text by Chris DAVIS and published by City University of HK Press. This book was released on 2024-07-17 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2022, John Maeda was awarded an Honorary Doctor of Engineering from the City University of Hong Kong. It was just one of many honors he has received in a multifaceted career encompassing art, science, business, and education in prestigious locales including the Massachusetts Institute of Technology, Rhode Island School of Design, and Silicon Valley. Dr Maeda has published several books on topics like simplicity and artificial intelligence, and he frequently shares his observations about design, technology, leadership, and more as a guest speaker and key opinion leader.