Microsoft Ai Studio Tutorial For Beginners

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Microsoft Ai Studio Tutorial For Beginners

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Author : StoryBuddiesPlay
language : en
Publisher: StoryBuddiesPlay
Release Date : 2025-04-22

Microsoft Ai Studio Tutorial For Beginners written by StoryBuddiesPlay and has been published by StoryBuddiesPlay this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-22 with Computers categories.

Unlock the full potential of Microsoft AI Studio with this beginner-friendly tutorial ebook. Whether you’re new to AI or looking to expand your skills, this guide walks you through every essential step from setting up your Azure account and exploring the AI Studio interface to importing data, building and training models, and deploying AI solutions. Learn how to design custom workflows with Prompt Flow, test generative AI in the Playground, and integrate AI models seamlessly into real-world applications. Packed with practical examples and best practices, this ebook is your gateway to mastering AI development on Microsoft’s powerful cloud platform. Microsoft AI Studio tutorial, AI model training, Azure AI Studio beginner, AI deployment Microsoft, generative AI Playground, Prompt Flow Microsoft, AI data management, AI integration tutorial, Microsoft Azure AI, AI project setup

Learning Microsoft Azure

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Author : Jonah Carrio Andersson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-11-20

Learning Microsoft Azure written by Jonah Carrio Andersson 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 2023-11-20 with Computers categories.

If your organization plans to modernize services and move to the cloud from legacy software or a private cloud on premises, this book is for you. Software developers, solution architects, cloud engineers, and anybody interested in cloud technologies will learn fundamental concepts for cloud computing, migration, transformation, and development using Microsoft Azure. Author and Microsoft MVP Jonah Carrio Andersson guides you through cloud computing concepts and deployment models, the wide range of modern cloud technologies, application development with Azure, team collaboration services, security services, and cloud migration options in Microsoft Azure. You'll gain insight into the Microsoft Azure cloud services that you can apply in different business use cases, software development projects, and modern solutions in the cloud. You'll also become fluent with Azure cloud migration services, serverless computing technologies that help your development team work productively, Azure IoT, and Azure cognitive services that make your application smarter. This book also provides real-world advice and best practices based on the author's own Azure migration experience. Gain insight into which Azure cloud service best suits your company's particular needs Understand how to use Azure for different use cases and specific technical requirements Start developing cloud services, applications, and solutions in the Azure environment Learn how to migrate existing legacy applications to Microsoft Azure

Microsoft Azure Essentials Azure Machine Learning

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Author : Jeff Barnes
language : en
Publisher: Microsoft Press
Release Date : 2015-04-25

Microsoft Azure Essentials Azure Machine Learning written by Jeff Barnes and has been published by Microsoft Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-25 with Computers categories.

Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.

Deep Learning With Azure

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Author : Mathew Salvaris
language : en
Publisher:
Release Date : 2018

Deep Learning With Azure written by Mathew Salvaris and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Microsoft Azure (Computing platform) categories.

Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI?Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll LearnBecome familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AIUse pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more)Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolvingDiscover the options for training and operationalizing deep learning models on Azure Who This Book Is ForProfessional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.

Microsoft Azure Ai A Beginner S Guide

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Author : Rekha Kodali
language : en
Publisher: BPB Publications
Release Date : 2022-04-21

Microsoft Azure Ai A Beginner S Guide written by Rekha Kodali and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-21 with Computers categories.

Explore Azure AI Platform KEY FEATURES ● Easy-to-follow tutorial for getting started with the Azure AI platform. ● Integrated platform for developing, deploying, and managing AI apps. ● Includes real-world scenarios and use-cases to fully explore Azure AI Platform. DESCRIPTION Microsoft Azure AI A Beginner's Guide explains the fundamentals of Azure AI and some more advanced topics. The sole objective of the book is to provide hands-on experience working with the various services, APIs, and tools available in the Azure AI Platform. This book begins by discussing the fundamentals of the Azure AI platform and the essential principles behind the Azure AI ecosystem and services. Readers will become familiar with the essential services, use cases, and examples provided by Azure AI Platform and Services, including Azure Cognitive Services, Azure Computer Vision, Azure Applied AI Services, and Azure Machine Learning. The author focuses on teaching how to utilize Azure Cognitive services to construct intelligent apps, including Image Processing, Object Detection, Text Recognition, OCR, Spatial Analysis, and Face Recognition using Computer Vision. Readers can investigate Azure Applied AI Services, including Form Recognizer, Metrics Advisor, Cognitive Search, Immersive Reader, Video Analyzer, and Azure Bot Service. Bot Framework and the Bot Framework Emulator will be explored in further detail, and how they can be used in AI applications to improve their conversational user interfaces. With Azure Machine Learning Studio, you will also learn to incorporate machine learning into your enterprise-level applications. WHAT YOU WILL LEARN ● Get familiar with Azure AI Platform and the cognitive capabilities of Azure. ● Learn to create apps that can process photos, detect faces, and detect objects. ● Utilize OCR, handwriting recognition, and spatial analysis in your development. ● Learn about Azure AI services like Form Recognizer, Metrics Advisor, Cognitive Search, Azure Immersive Reader, and Video Analyzer. ● Try out several NLP applications with the Azure BOT framework. WHO THIS BOOK IS FOR This book teaches AI developers, machine learning engineers, .NET developers, and architects how to swiftly develop intelligent applications utilizing the Azure AI Platform. Knowledge of.NET or.NET Core is strongly advised to get the most out of the book. TABLE OF CONTENTS 1 .Azure AI Platform and Services 2. Azure Computer Vision - Image Analysis, Processing, Content Moderation, Object and Face Detection 3. Computer Vision - Text Recognition, Optical Character Recognition, Spatial Analysis 4. Azure Cognitive Services - Custom Applications leveraging Decision, Language, Speech, Web Search 5. Azure Applied AI Services 6. Azure Applied AI Services -BOTs– A Brief Introduction 7. Machine Learning-Infusing ML in Custom Applications using ML.NET 8. Machine Learning - Using Azure ML Studio

Building Neo4j Powered Applications With Llms

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Author : Ravindranatha Anthapu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-06-20

Building Neo4j Powered Applications With Llms written by Ravindranatha Anthapu 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 2025-06-20 with Computers categories.

A comprehensive guide to building cutting-edge generative AI applications using Neo4j's knowledge graphs and vector search capabilities Key Features Design vector search and recommendation systems with LLMs using Neo4j GenAI, Haystack, Spring AI, and LangChain4j Apply best practices for graph exploration, modeling, reasoning, and performance optimization Build and consume Neo4j knowledge graphs and deploy your GenAI apps to Google Cloud Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionEmbark on an expert-led journey into building LLM-powered applications using Retrieval-Augmented Generation (RAG) and Neo4j knowledge graphs. Written by Ravindranatha Anthapu, Principal Consultant at Neo4j, and Siddhant Agrawal, a Google Developer Expert in GenAI, this comprehensive guide is your starting point for exploring alternatives to LangChain, covering frameworks such as Haystack, Spring AI, and LangChain4j. As LLMs (large language models) reshape how businesses interact with customers, this book helps you develop intelligent applications using RAG architecture and knowledge graphs, with a strong focus on overcoming one of AI’s most persistent challenges—mitigating hallucinations. You'll learn how to model and construct Neo4j knowledge graphs with Cypher to enhance the accuracy and relevance of LLM responses. Through real-world use cases like vector-powered search and personalized recommendations, the authors help you build hands-on experience with Neo4j GenAI integrations across Haystack and Spring AI. With access to a companion GitHub repository, you’ll work through code-heavy examples to confidently build and deploy GenAI apps on Google Cloud. By the end of this book, you’ll have the skills to ground LLMs with RAG and Neo4j, optimize graph performance, and strategically select the right cloud platform for your GenAI applications.What you will learn Design, populate, and integrate a Neo4j knowledge graph with RAG Model data for knowledge graphs Integrate AI-powered search to enhance knowledge exploration Maintain and monitor your AI search application with Haystack Use LangChain4j and Spring AI for recommendations and personalization Seamlessly deploy your applications to Google Cloud Platform Who this book is for This LLM book is for database developers and data scientists who want to leverage knowledge graphs with Neo4j and its vector search capabilities to build intelligent search and recommendation systems. Working knowledge of Python and Java is essential to follow along. Familiarity with Neo4j, the Cypher query language, and fundamental concepts of databases will come in handy.

Artificial Intelligence With Microsoft Power Bi

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Author : Jen Stirrup
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-03-28

Artificial Intelligence With Microsoft Power Bi written by Jen Stirrup 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 2024-03-28 with Computers categories.

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization. Springboarding from the skills that you already possess, this book adds AI to your organization's technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you'll learn how to choose the right model for your AI work and identify its value and validity. Use Power BI to build a good data model for AI Demystify the AI terminology that you need to know Identify AI project roles, responsibilities, and teams for AI Use AI models, including supervised machine learning techniques Develop and train models in Azure ML for consumption in Power BI Improve your business AI maturity level with Power BI Use the AI feedback loop to help you get started with the next project

Low Code Ai

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Author : Gwendolyn Stripling
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-09-13

Low Code Ai written by Gwendolyn Stripling 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 2023-09-13 with Computers categories.

Take a data-first and use-case–driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems. Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data; feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. You'll learn how to: Distinguish between structured and unstructured data and the challenges they present Visualize and analyze data Preprocess data for input into a machine learning model Differentiate between the regression and classification supervised learning models Compare different ML model types and architectures, from no code to low code to custom training Design, implement, and tune ML models Export data to a GitHub repository for data management and governance

Microsoft Power Pages In Action

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Author : Faisal Hussona
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-28

Microsoft Power Pages In Action written by Faisal Hussona 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 2024-06-28 with Computers categories.

Master low-code web app development with Power Pages, learn to customize web apps using Liquid and JavaScript guided by step-by-step instructions and real-world examples. Key Features Build custom web apps effortlessly with Power Pages' low-code platform Learn to integrate external services and databases using codeless cloud flows Extend your web apps with customizable code using ChatGPT and Copilot Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMicrosoft Power Apps Pages in Action is a comprehensive beginner's guide for effortlessly building and customizing functional-rich web apps. Packed with real-world examples, it offers a practical understanding of the Power Pages environment. You’ll understand web pages by creating data tables and forms, progress to adding web pages, and delve into advanced techniques for seamlessly integrating web apps. Now, you’ll learn how to create responsive web pages, automate web apps, and use ChatGPT-assisted coding with code snippets for common requirements or needs. As you progress, you'll be guided on crafting portals and websites, encompassing the utilization of various functionalities and layouts. Progressively, you’ll discover how to seamlessly integrate them into your web pages across multiple Microsoft technologies, including Dataverse and Power Automate. Towards the end, you'll also learn how to implement cloud flows to provide access to external services and use cloud flows to provide user experiences running processes off the page. By the end of the book, you’ll have a solid understanding of Power Pages and be able to create web applications tailored to your unique needs.What you will learn Build interactive web pages and portals using Power Pages Establish secure web sites with robust configurations for data integrity Implement responsive design for adaptable apps on different devices Integrate Power Pages with external services Learn to code using Power Pages tools and ChatGPT assistance Implement charts and custom styling in your web apps Discover where and how to use Liquid and JavaScript effectively Develop and utilize web templates for efficient app design Who this book is for This book is the ultimate guide for citizen developers aiming to build functionally rich and responsive web apps with Power Pages. With clear and concise guidance, it caters to both beginners and experienced developers, offering practical insights into every aspect of web app development. Whether you're new to the field or seeking advanced techniques, this book equips you with the skills you need to create powerful and user-friendly web apps tailored to your unique needs.

Adversarial Ai Attacks Mitigations And Defense Strategies

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Author : John Sotiropoulos
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-26

Adversarial Ai Attacks Mitigations And Defense Strategies written by John Sotiropoulos 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 2024-07-26 with Computers categories.

“The book not only explains how adversarial attacks work but also shows you how to build your own test environment and run attacks to see how they can corrupt ML models. It's a comprehensive guide that walks you through the technical details and then flips to show you how to defend against these very same attacks.” – Elaine Doyle, VP and Cybersecurity Architect, Salesforce Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Understand the unique security challenges presented by predictive and generative AI Explore common adversarial attack strategies as well as emerging threats such as prompt injection Mitigate the risks of attack on your AI system with threat modeling and secure-by-design methods 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 you with the skills to secure AI technologies, moving beyond research hype or business-as-usual activities. Learn how to defend AI and LLM systems against manipulation and intrusion through adversarial attacks such as poisoning, trojan horses, and model extraction, leveraging DevSecOps, MLOps, and other methods to secure systems. This strategy-based book is a comprehensive guide to AI security, combining structured frameworks with practical examples to help you identify and counter adversarial attacks. Part 1 introduces the foundations of AI and adversarial attacks. Parts 2, 3, and 4 cover key attack types, showing how each is performed and how to defend against them. Part 5 presents secure-by-design AI strategies, including threat modeling, MLSecOps, and guidance aligned with OWASP and NIST. The book concludes with a blueprint for maturing enterprise AI security based on NIST pillars, addressing ethics and safety under Trustworthy AI. By the end of this book, you’ll be able to develop, deploy, and secure AI systems against the threat of adversarial attacks effectively.What you will learn Set up a playground to explore how adversarial attacks work Discover how AI models can be poisoned and what you can do to prevent this Learn about the use of trojan horses to tamper with and reprogram models Understand supply chain risks Examine how your models or data can be stolen in privacy attacks See how GANs are weaponized for Deepfake creation and cyberattacks Explore emerging LLM-specific attacks, such as prompt injection Leverage DevSecOps, MLOps and MLSecOps to secure your AI system Who this book is for This book tackles AI security from both angles - offense and defence. AI 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 to AI and mitigate the 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.