Programming Large Language Models With Azure Open Ai
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Programming Large Language Models With Azure Open Ai
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Author : Francesco Esposito
language : en
Publisher: Microsoft Press
Release Date : 2024-04-03
Programming Large Language Models With Azure Open Ai written by Francesco Esposito and has been published by Microsoft Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-03 with Computers categories.
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
Clean Architecture With Net
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Author : Dino Esposito
language : en
Publisher: Microsoft Press
Release Date : 2024-03-12
Clean Architecture With Net written by Dino Esposito and has been published by Microsoft Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-12 with Computers categories.
Understand what to do at any point in developing a clean .NET architecture Master advanced .NET techniques with a focus on actual value delivered by working within a modular, clean architecture. Microsoft Data Platform MVP Dino Esposito explains key clean architecture concepts with a mix of pragmatism and design discipline and helps you solidify your knowledge through a real-world project. Starting with an explanation of the quest for modular software architecture continuing through the methodology of domain-driven design (DDD), Esposito emphasizes the role that modularization plays in managing complexity in software development. Breaking down the layers of an architecture that is modular and maintainable, he presents a sample project that is not simply another to-do list, but an actual tool for the reader. Ultimately, an exploration of common dilemmas for both developers and operations brings together historical developments with real solutions for today. Microsoft Data Platform MVP Dino Esposito helps you: · Understand the relevance of modular software architecture in the history of software · Review domain-driven design concepts both, strategic and practical · Apply modular analysis techniques to your development · Make the most of layered architecture · Make the most of layered architecture that is modular and maintainable · Explore in detail the individual layers—presentation, application, domain and infrastructure · Make sense of domain services to separate raw persistence from persistence-related business tasks · Make your way through a series of C# best-practices for modeling classes from real-world entities · Understand the benefits of microservices versus modular monoliths · Understand the analysis of technical shortcuts and benefits of long-term technical investment · Understand client-side, server-side and other common deployment dilemmas · Set up your architecture, test your conclusions, and find even more help
Responsible Ai In The Enterprise
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Author : Adnan Masood
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-07-31
Responsible Ai In The Enterprise written by Adnan Masood 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 2023-07-31 with Computers categories.
Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfalls Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn ethical AI principles, frameworks, and governance Understand the concepts of fairness assessment and bias mitigation Introduce explainable AI and transparency in your machine learning models Book DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations. By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.What you will learn Understand explainable AI fundamentals, underlying methods, and techniques Explore model governance, including building explainable, auditable, and interpretable machine learning models Use partial dependence plot, global feature summary, individual condition expectation, and feature interaction Build explainable models with global and local feature summary, and influence functions in practice Design and build explainable machine learning pipelines with transparency Discover Microsoft FairLearn and marketplace for different open-source explainable AI tools and cloud platforms Who this book is for This book is for data scientists, machine learning engineers, AI practitioners, IT professionals, business stakeholders, and AI ethicists who are responsible for implementing AI models in their organizations.
C Interview Guide
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Author : Konstantin Semenenko
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-08
C Interview Guide written by Konstantin Semenenko 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 2024-03-08 with Computers categories.
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.
Azure Openai Essentials
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Author : Amit Mukherjee
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-02-27
Azure Openai Essentials written by Amit Mukherjee and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Computers categories.
Build innovative, scalable, and ethical AI solutions by harnessing the full potential of generative AI with this exhaustive guide Key Features Explore the capabilities of Azure OpenAI’s LLMs Craft end-to-end applications by utilizing the synergy of Azure OpenAI and Cognitive Services Design enterprise-grade GenAI solutions with effective prompt engineering, fine-tuning, and AI safety measures Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionFind out what makes Azure OpenAI a robust platform for building AI-driven solutions that can transform how businesses operate. Written by seasoned experts from Microsoft, this book will guide you in understanding Azure OpenAI from fundamentals through to advanced concepts and best practices. The book begins with an introduction to large language models (LLMs) and the Azure OpenAI Service, detailing how to access, use, and optimize its models. You'll learn how to design and implement AI-driven solutions, such as question-answering systems, contact center analytics, and GPT-powered search applications. Additionally, the chapters walk you through advanced concepts, including embeddings, fine-tuning models, prompt engineering, and building custom AI applications using LangChain and Semantic Kernel. You'll explore real-world use cases such as QnA systems, document summarizers, and SQLGPT for database querying, as well as gain insights into securing and operationalizing these solutions in enterprises. By the end of this book, you'll be ready to design, develop, and deploy scalable AI solutions, ensuring business success through intelligent automation and data-driven insights.What you will learn Understand the concept of large language models and their capabilities Interact with different models in Azure OpenAI using APIs or web interfaces Use content filters and mitigations to prevent harmful content generation Develop solutions with Azure OpenAI for content generation, summarization, semantic search, NLU, code and image generation and analysis Integrate Azure OpenAI with other Azure Cognitive services for enhanced functionality Apply best practices for data privacy, security, and prompt engineering with Azure OpenAI Who this book is for This book is for software developers, data scientists, AI engineers, ML engineers, system architects, LLM engineers, IT professionals, product managers, and business professionals who want to learn how to use Azure OpenAI to create innovative solutions with generative AI. To fully benefit from this book, you must have both an Azure subscription and Azure OpenAI access, along with knowledge of Python.
Azure Openai Service For Cloud Native Applications
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Author : Adrián González Sánchez
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-06-27
Azure Openai Service For Cloud Native Applications written by Adrián González Sánchez 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 2024-06-27 with Computers categories.
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
Data Labeling In Machine Learning With Python
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Author : Vijaya Kumar Suda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-01-31
Data Labeling In Machine Learning With Python written by Vijaya Kumar Suda 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 2024-01-31 with Computers categories.
Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling Key Features Generate labels for regression in scenarios with limited training data Apply generative AI and large language models (LLMs) to explore and label text data Leverage Python libraries for image, video, and audio data analysis and data labeling Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.What you will learn Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data Understand how to use Python libraries to apply rules to label raw data Discover data augmentation techniques for adding classification labels Leverage K-means clustering to classify unsupervised data Explore how hybrid supervised learning is applied to add labels for classification Master text data classification with generative AI Detect objects and classify images with OpenCV and YOLO Uncover a range of techniques and resources for data annotation Who this book is for This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.
Data Science Solutions On Azure
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Author : Julian Soh
language : en
Publisher: Springer Nature
Release Date : 2024-11-18
Data Science Solutions On Azure written by Julian Soh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-18 with Computers categories.
This revamped and updated book focuses on the latest in AI technology—Generative AI. It builds on the first edition by moving away from traditional data science into the area of applied AI using the latest breakthroughs in Generative AI. Based on real-world projects, this edition takes a deep look into new concepts and approaches such as Prompt Engineering, testing and grounding of Large Language Models, fine tuning, and implementing new solution architectures such as Retrieval Augmented Generation (RAG). You will learn about new embedded AI technologies in Search, such as Semantic and Vector Search. Written with a view on how to implement Generative AI in software, this book contains examples and sample code. In addition to traditional Data Science experimentation in Azure Machine Learning (AML) that was covered in the first edition, the authors cover new tools such as Azure AI Studio, specifically for testing and experimentation with Generative AI models. What's New in this Book Provides new concepts, tools, and technologies such as Large and Small Language Models, Semantic Kernel, and Automatic Function Calling Takes a deeper dive into using Azure AI Studio for RAG and Prompt Engineering design Includes new and updated case studies for Azure OpenAI Teaches about Copilots, plugins, and agents What You'll Learn Get up to date on the important technical aspects of Large Language Models, based on Azure OpenAI as the reference platform Know about the different types of models: GPT3.5 Turbo, GPT4, GPT4o, Codex, DALL-E, and Small Language Models such as Phi-3 Develop new skills such as Prompt Engineering and fine tuning of Large/Small Language Models Understand and implement new architectures such as RAG and Automatic Function Calling Understand approaches for implementing Generative AI using LangChain and Semantic Kernel See how real-world projects help you identify great candidates for Applied AI projects, including Large/Small Language Models Who This Book Is For Software engineers and architects looking to deploy end-to-end Generative AI solutions on Azure with the latest tools and techniques.
Modern Data Analytics In Excel
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Author : George Mount
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-04-26
Modern Data Analytics In Excel written by George Mount 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 2024-04-26 with Computers categories.
If you haven't modernized your data cleaning and reporting processes in Microsoft Excel, you're missing out on big productivity gains. And if you're looking to conduct rigorous data analysis, more can be done in Excel than you think. This practical book serves as an introduction to the modern Excel suite of features along with other powerful tools for analytics. George Mount of Stringfest Analytics shows business analysts, data analysts, and business intelligence specialists how to make bigger gains right from your spreadsheets by using Excel's latest features. You'll learn how to build repeatable data cleaning workflows with Power Query, and design relational data models straight from your workbook with Power Pivot. You'll also explore other exciting new features for analytics, such as dynamic array functions, AI-powered insights, and Python integration. Learn how to build reports and analyses that were previously difficult or impossible to do in Excel. This book shows you how to: Build repeatable data cleaning processes for Excel with Power Query Create relational data models and analysis measures with Power Pivot Pull data quickly with dynamic arrays Use AI to uncover patterns and trends from inside Excel Integrate Python functionality with Excel for automated analysis and reporting
Azure Ai Services At Scale For Cloud Mobile And Edge
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Author : Simon Bisson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-04-11
Azure Ai Services At Scale For Cloud Mobile And Edge written by Simon Bisson 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 2022-04-11 with Computers categories.
Take advantage of the power of cloud and the latest AI techniques. Whether you're an experienced developer wanting to improve your app with AI-powered features or you want to make a business process smarter by getting AI to do some of the work, this book's got you covered. Authors Anand Raman, Chris Hoder, Simon Bisson, and Mary Branscombe show you how to build practical intelligent applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. This book shows you how cloud AI services fit in alongside familiar software development approaches, walks you through key Microsoft AI services, and provides real-world examples of AI-oriented architectures that integrate different Azure AI services. All you need to get started is a working knowledge of basic cloud concepts. Become familiar with Azure AI offerings and capabilities Build intelligent applications using Azure Cognitive Services Train, tune, and deploy models with Azure Machine Learning, PyTorch, and the Open Neural Network Exchange (ONNX) Learn to solve business problems using AI in the Power Platform Use transfer learning to train vision, speech, and language models in minutes