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
About the Author:
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).
