Hands-on Azure Cognitive Services : Applying AI and Machine Learning for Richer Applications

Use this hands-on guide book to learn and explore cognitive APIs developed by Microsoft and provided with the Azure platform. This book gets you started working with Azure Cognitive Services. You will not only become familiar with Cognitive Services APIs for applications, but you will also be exposed to methods to make your applications intelligent for deployment in businesses. The book starts with the basic concepts of Azure Cognitive Services and takes you through its features and capabilities. You then learn how to work inside the Azure Marketplace for Bot Services, Cognitive Services, and Machine Learning. You will be shown how to build an application to analyze images and videos, and you will gain insight on natural language processing (NLP). Speech Services and Decision Services are discussed along with a preview of Anomaly Detector. You will go through Bing Search APIs and learn how to deploy and host services by using containers. And you will learn how to use Azure Machine Learning and create bots for COVID-19 safety, using Azure Bot Service. After reading this book, you will be able to work with datasets that enable applications to process various data in the form of images, videos, and text. What You Will Learn Discover the options for training and operationalizing deep learning models on Azure Be familiar with advanced concepts in Azure ML and the Cortana Intelligence Suite architecture Understand software development kits (SKDs) Deploy an application to Azure Kubernetes Service Who This Book Is For Developers working on a range of platforms, from .NET and Windows to mobile devices, as well as data scientists who want to explore and learn more about deep learning and implement it using the Microsoft AI platform Table of Contents About the Authors About the Technical Reviewer Acknowledgments Introduction Chapter 1: The Power of Cognitive Services Overview of Azure Cognitive Services Why Azure Cognitive Services Exploring the Cognitive Services APIs: Vision, Speech, Language, Web Search, and Decision Vision APIs Computer Vision Custom Vision Face Form Recognizer Video Indexer Speech APIs Speech Service Speaker Recognition (Preview) Language APIs Immersive Reader Language Understanding (LUIS) QnA Maker Text Analytics Translator Web Search APIs Bing Search APIs Bing Web Search Bing Custom Search Bing Image Search Bing Entity Search Bing News Search Bing Video Search Bing Visual Search Bing Autosuggest Bing Spell Check Bing Local Business Search Decision APIs Anomaly Detector (Preview) Content Moderator Personalizer Overview of Machine Learning Understanding the Use Cases The COVID-19 SmartApp Scenario Summary Chapter 2: The Azure Portal for Cognitive Services Getting Started with Azure Portal and Azure Cognitive Services Getting Started with Azure Cognitive Services Azure Marketplace: An Overview of AI + Machine Learning Understanding Software Development Kits (SDKs): To Get Started with Your Favorite Programing Language Setting Up Your Visual Studio Template Summary Chapter 3: Vision – Identify and Analyze Images and Videos Understanding the Vision APIs with Computer Vision Analyzing Images Start Diving for Computer Vision Working with APIs Identifying a Face Test Using the API Console Test Using a Demo Page Implement It Using Code Understanding the Working Behavior of Vision APIs for Video Analysis Microsoft Azure Video Indexer Summary Chapter 4: Language – Understand Unstructured Text and Models Creating and Understanding Language Models Enrichment in Progress – JFK Files Demo The Muppet Models – Transformers for NLP Named Entity Recognition with Fine-Tuned BERT Summary of the Language API Chapter 5: Speech – Talk to Your Application Understanding Speech and Speech Services Comprehensive Privacy and Security Getting Started Translating Speech Real Time into Your Application Speech to Text – Converting Spoken Audio to Text for Interaction Cognitive Speech Search with LUIS and Speech Studio Summary of the Speech API Chapter 6: Decision – Make Smarter Decisions in Your Applications Decision Services and APIs Content Moderator Service Trying It Out – Building Content Moderators Moderating Text Using Content Moderator Service Moderating Text – Invoking the API Personalizer Service Trying It Out – Building a Movie Personalizer Anomaly Detector Service Try It Out – Anomaly Detector Demo Metrics Advisor (Preview) Summary and Conclusion References and Further Reading Chapter 7: Search – Add Search Capabilities to Your Application The Search Ecosystem Azure Cognitive Search Searching with Azure Cognitive Search Testing Azure Cognitive Search Integrating Azure Cognitive Search in Your Notebooks Searching with Bing Web Search Summary and Conclusion References and Further Reading Chapter 8: Deploy and Host Services Using Containers Cognitive Services Containers Hosting Cognitive Services Containers Running a Language Service Container Running an Anomaly Detector Service Container Working with Azure Container Instances Deploying a Cognitive Services Container with Azure Kubernetes Service Summary and Conclusion References and Further Reading Chapter 9: Azure Bot Services The Azure Bot Services Ecosystem Building Azure Service COVID-19 Bot Augmenting the Bot Knowledge Base from the Web Conclusion and Summary References and Further Reading Chapter 10: Azure Machine Learning Azure Machine Learning Stack Hello World with Azure Machine Learning Creating a Machine Learning Model for Classification Classification Model Using Azure Machine Learning Designer Conclusion and Summary References and Further Reading Index This book is your systematic cloud migration guide. Experiences shared by the author are drawn from real-life migration projects and contain practical advice, as well as step-by-step architecture, design, and technical implementation instructions using sample application code on GitLab. Following the guidance in this book will provide much needed support to your teams, and help you successfully complete the application cloud migration journey. Systematic Cloud Migration consists of four major parts. Part one starts with a fundamental introduction of cloud computing to establish the context for migration, including paradigm changes in five important areas: software application, DevSecOps, operations, infrastructure, and security. And these are the areas that the book follows throughout. Next, it introduces a real-life migration process that your team can follow. Part two presents the migration process for the application code, including architecture diagrams and presented by demo application code and supporting infrastructure in AWS cloud. Part three dives into DevSecOps and automation. In addition to concepts, a real-life migration diagram and sample pipeline code implemented with GitLab are include. Part four deals with efficient cloud operations. Each chapter has a practical structure: objectives, roles, inputs, process/activities, outputs/deliverables, best practices, and summary. There is a wealth of cloud production-grade template style artifacts that can be used as is. What You Will Learn Design applications in the cloud, including determining the design criteria (e.g., solution cost is a design criterion, same as security, and is not an afterthought)Understand the major migration areas: software development (application code, data, integration, and configuration), software delivery (pipeline and automation), and software operations(observability)Migrate each application element: client and business components code, data, integration and services, logging, monitoring, alerting, as well as configurationsUnderstand cloud-critical static application security testing (SAST), dynamic application security testing (DAST), containers compliance and security scanning, and open source dependency testingKnow the directions and implementation details on cost-efficient, automated, cloud-native software operations Who This Book Is For Primarily designed with software developers, team leads, development managers, DevOps engineers, and software architects in mind. Their day-to-day activities include architecting, designing, developing, delivering, and operating software in the cloud environment. In addition, this book will benefit infrastructure, network, security, and operations engineers, who in turn, can provide better support for the software development product teams. Use this hands-on guide book to learn and explore cognitive APIs developed by Microsoft and provided with the Azure platform. This book gets you started working with Azure Cognitive Services. You will not only become familiar with Cognitive Services APIs for applications, but you will also be exposed to methods to make your applications intelligent for deployment in businesses.The book starts with the basic concepts of Azure Cognitive Services and takes you through its features and capabilities. You then learn how to work inside the Azure Marketplace for Bot Services, Cognitive Services, and Machine Learning. You will be shown how to build an application to analyze images and videos, and you will gain insight on natural language processing (NLP). Speech Services and Decision Services are discussed along with a preview of Anomaly Detector. You will go through Bing Search APIs and learn how to deploy and host services by using containers. And you will learn how to use Azure Machine Learning and create bots for COVID-19 safety, using Azure Bot Service.After reading this book, you will be able to work with datasets that enable applications to process various data in the form of images, videos, and text.What You Will Learn• Discover the options for training and operationalizing deep learning models on Azure• Be familiar with advanced concepts in Azure ML and the Cortana Intelligence Suite architecture• Understand software development kits (SDKs)• Deploy an application to Azure Kubernetes ServiceWho This Book Is ForDevelopers working on a range of platforms, from .NET and Windows to mobile devices, as well as data scientists who want to explore and learn more about deep learning and implement it using the Microsoft AI platform