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

ISBN-13: 9781484272480 / Angielski / Miękka / 2021 / 329 str.

Ed Price; Adnan Masood; Gaurav Aroraa

Opis

Intermediate-Advanced user level

Spis treści

​Chapter 1:  The Power of Cognitive Services

Chapter Goal: This first chapter sets up the values, reasons, and impacts you can achieve through Microsoft Azure Cognitive Services. It provides an overview of the features and capabilities. The chapter also introduces you to our case study and structures that we’ll use throughout the rest of the book.

No of pages: 14

Sub - Topics    

1.      Overview of Azure Cognitive Services

2.      Understanding the Use Cases

3.      Exploring the Cognitive Services APIs: Vision, Speech, Language, Search, and Decision

4.      Overview of Machine Leaning

5.      The COVID-19 SmartApp Scenario

Chapter 2:  The Azure Portal for Cognitive Services

Chapter Goal: The aim of this chapter to get started with Microsoft Cognitive services by exploring the Azure Portal. This chapter will explore the Cognitive Azure Portal and some of the common features. Finally, the chapter will take you inside the Azure Marketplace for Bot Service, Cognitive Services, and Machine Learning.

No of pages: 18

Sub - Topics    

1.       Getting started with Azure Portal and Microsoft Cognitive Services

2.      Azure Marketplace – an overview of AI + Machine Learning

3.      Getting started with Azure Bot Service

4.      Understanding software development kits (SDKs) – to get started with a favorite programing language [Ref. https://docs.microsoft.com/en-us/azure/cognitive-services/]

5.      Setting up your Visual Studio template 

Chapter 3:  Vision – Identify and Analyze Images and Videos

Chapter Goal: This chapter will provide insight on Computer Vision with a full of hands-on example, where we build an application to analyze an Image. There are two features currently in preview that this chapter will also cover: Form Recognizer and Ink Recognizer.  

No of pages: 24

Sub - Topics    

1.       Understanding the Vision API with Computer Vision

2.      Analyzing images

3.      Identifying a face

4.      Understanding the working behavior of vision APIs for Video Analysis

5.      Recognizing forms, tables, and ink

6.      Summary of the Vision API

Chapter 4:  Language – Gain an Understanding of Unstructured Text and Models

Chapter Goal: This chapter will provide insight on NLP (Natural language processing) by evaluating user sentiments. The chapter will also touch preview features – including Immersive Reader.  

No of pages: 20

Sub - Topics    

1.      Creating and understanding language models

2.      Training language models

3.      Translating text to create your own translator application

4.      Using QnA Maker to host conversational discussions about your data

5.      Using Immersive Reader to understand text via audio and visual cues

6.      Summary of the Language API

Chapter 5:  Speech – Talk to Your Application

Chapter Goal: This chapter will provide insight on speech services by evaluating translating text to speech and vice versa. Enabling a speaker and translating into multiple languages. The chapter will also touch a preview feature – Speaker Recognition. The Bing speech feature will not be covered as it is retiring soon.  

No of pages: 18

Sub - Topics    

1.      Understanding speech and speech services

2.      Converting speech into text and vice versa

3.      Translating speech real-time into your application

4.      Identifying the speaker from speech using Speaker Recognition

5.      Customizing speech

6.      Summary of the Speech API

Chapter 6:  Decision – Make Smarter Decisions In Your Applications

Chapter Goal: This chapter will provide insight on decision services by adding content a moderation facility in the application. The chapter will also touch on a preview feature – Anomaly Detector.  

No of pages: 17

Sub - Topics    

1.      Understanding the decision service and decision APIs

2.      Creating an auto Content Moderator application

3.      Creating personalized experiences with the Personalizer

4.      Identifying future problems with the Anomaly Detector

5.      Summary of the Decision API 

Chapter 7:  Search – Add Search Capabilities to Your Application

Chapter Goal: This chapter will provide insight on Bing Search APIs by adding various search functionalities to the application.  

No of pages: 18

Sub - Topics    

1.      Understanding search and the Bing Search APIs

2.      Creating a smart application by adding Bing Search

3.      Suggesting a user with auto suggestions

4.      Summary of the Search API 

Chapter 8:  Deploy and Host Services Using Containers

Chapter Goal: This chapter will provide a complete insight on Cognitive Services containers. In this chapter, we will highlight the key feature by creating an application. The application will deploy using Docker.

No of pages: 22

Sub - Topics    

1.      Getting started with Cognitive Services containers

2.      Understanding deployment and how to deploy and run a container on an Azure container instance

3.      Understand Docker compose and use it to deploy multiple containers

4.      Understanding Azure Kubernetes Service and how to deploy an application to Azure Kubernetes Service

Chapter 9:  Azure Bot Service

Chapter Goal: This chapter will provide insight on Bot Service by creating the COVID-19 Bot.  

No of pages: 24

Sub - Topics    

1.      Understanding Azure Bot services

2.      Create a COVID-19 Bot using Azure Bot Service

3.      Using the Azure Bot Builder SDK. Reference: https://docs.microsoft.com/en-us/azure/bot-service/dotnet/bot-builder-dotnet-sdk-quickstart?view=azure-bot-service-4.0

Chapter 10:  Azure Machine Learning

Chapter Goal: This chapter will lead the reader to fully understand Azure Machine Learning and how to use it. You can train your application to learn without being explicitly programmed. We will include forecasts and predictions. The chapter will cover a preview feature – Azure Machine Learning designer.

No of pages: 22

Sub - Topics    

1.      Building models with no-code, using the Azure Machine Learning designer

2.      Publishing to Jupyter notebooks

3.      Building ML models in Python or R

4.      The ML Visual Studio Code extension

5.      Commanding the ML CLI

6.      Summary of ML

O autorze

Ed Price is Senior Program Manager in Engineering at Microsoft, with an MBA degree in technology management. Previously, he led Azure Global’s efforts to publish key architectural guidance, ran Microsoft customer feedback programs for Azure Development and Data Services, and was a technical writer at Microsoft for six years, helping lead TechNet Wiki. Ed now leads Microsoft’s efforts to publish reference architectures on the Azure Architecture Center (including a strong focus on AI architectures). He is an instructor at Bellevue College, where he teaches design and computer science. At Microsoft, he also helps lead volunteer efforts to teach thousands of students how to code each year, focusing on girls and minorities. Ed is a co-author of six books, including Azure Cloud Native Architecture Mapbook, Cloud Debgging and Profiling in Microsoft Azure (Apress), and Learn to Program with Small Basic.

Adnan Masood, PhD, is an Artificial Intelligence and Machine Learning researcher, Software Engineer, Microsoft regional Director, and Microsoft MVP for Artificial Intelligence. An international speaker and thought leader, Adnan currently works at UST as Chief AI Architect, and collaborates with Stanford Artificial Intelligence Lab and MIT AI Lab on building enterprise solutions. Adnan has authored four books, including Automated Machine Learning and Cognitive Computing Recipes (Apress).

Gaurav Aroraa is a Chief Technology officer at SCL, with Doctorate in Computer Science. Guarav is a Microsoft MVP award recipient. He is a lifetime member of the Computer Society of India (CSI), an advisory member and senior mentor at IndiaMentor, certified as a Scrum trainer and coach, ITIL-F certified, and PRINCE-F and PRINCE-P certified. Guarav is an open-source developer and a contributor to the Microsoft TechNet community. He has authored ten books, including Cloud Debugging and Profiling in Microsoft Azure (Apress).

Blurb

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.

You will:

• 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