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  • Book
  • © 2021

Beginning Azure Cognitive Services

Data-Driven Decision Making Through Artificial Intelligence

Apress

Authors:

(view affiliations)
  • Explains Cognitive Services and how to integrate them into your applications

  • Includes low-code and no-code examples involving the Microsoft Power Platform and Azure Logic Apps

  • Covers ethical considerations around making decisions through artificial intelligence

  • 3850 Accesses

Buying options

eBook
USD 54.99
Price excludes VAT (USA)
  • ISBN: 978-1-4842-7176-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD 69.99
Price excludes VAT (USA)

This is a preview of subscription content, access via your institution.

Table of contents (8 chapters)

  1. Front Matter

    Pages i-xxii
  2. Introducing Cognitive Services

    • Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
    Pages 1-17
  3. Prerequisites and Tools

    • Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
    Pages 19-48
  4. Vision

    • Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
    Pages 49-96
  5. Language in Cognitive Services

    • Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
    Pages 97-151
  6. Speech Services

    • Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
    Pages 153-192
  7. Power Platform and Cognitive Services

    • Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
    Pages 193-240
  8. Chatbots

    • Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
    Pages 241-280
  9. Ethics in AI

    • Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
    Pages 281-297
  10. Back Matter

    Pages 299-306

About this book

Get started with Azure Cognitive Services and its APIs that expose machine learning as a service. This book introduces the suite of Azure Cognitive Services and helps you take advantage of the proven machine learning algorithms that have been developed by experts and made available through Cognitive Services, easily integrating those algorithms into your own applications without having to develop the algorithms from scratch. The book also shows you how to use the algorithms provided by Cognitive Services to accelerate data analysis and development within your organization.  

The authors begin by introducing the tools and describing the steps needed to invoke libraries to analyze structured and unstructured text, speech, and pictures, and you will learn to create interactive chatbots using the Cognitive Services libraries. Each chapter contains the information you need to implement artificial intelligence (AI) via Azure Cognitive Services in your personal and professional projects. 

The book also covers ethical considerations that are becoming increasingly of concern when using AI to drive decision making. You will be introduced to tools such as FairLearn and InterpretML that can help you detect bias and understand the results your models are generating.

You will learn to:
  • Invoke the Cognitive Services APIs from a variety of languages and apps
  • Understand common design architectures for AI solutions in Azure
  • Decrease discrimination and bias when creating an AI-driven solution
  • Execute the examples within the book and learn how to extend those examples
  • Implement best practices for leveraging the Vision, Speech, and Language parts of the suite
  • Test Cognitive Services APIs via the Azure portal and using the Postman API tool
  • Execute AI from low-code and no-code platforms like Logic Apps and Microsoft’s Power Platform

Keywords

  • Cognitive Services
  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Chatbots
  • Sentiment Analysis
  • Cognitive Vision
  • Document Analysis
  • Cognitive Search
  • Cognitive Speech
  • Postman API
  • Ethics
  • Data Science
  • Docker Desktop Client
  • Pandas
  • Azure Data Studio
  • TensorFlow
  • Anomaly Detection
  • FairLearn
  • InterpretML
  • Differential Privacy

Authors and Affiliations

  • Houston, USA

    Alicia Moniz

  • Lexington, USA

    Matt Gordon

  • Oslo, Norway

    Ida Bergum

  • Berlin, Germany

    Mia Chang

  • Scottsdale, USA

    Ginger Grant

About the authors

Alicia Moniz is a Microsoft AI MVP, #KafkaOnAzure Evangelista, and active supporter of women in technology. She authors the blog HybridDataLakes.com, focused on cloud data learning resources, and produces content for the YouTube channel, #KafkaOnAzure. She is also on the Leadership Board for the Global AI community and is an organizer for Global AI Bootcamp - Houston Edition, a Microsoft AI-sponsored event. Alicia is active in the Microsoft User Group community and enjoys speaking on AI, SQLServer, #KafkaOnAzure, and personal branding for women in technology topics.

Matt Gordon is a Microsoft Data Platform MVP and has worked with SQL Server since 2000. He is the leader of the Lexington, KY Data Technology Group and a frequent domestic and international community speaker. He is an IDERA ACE alumnus and 2021 Friend of Redgate. His original data professional role was in database development, which quickly evolved into query tuning work that further evolved into being a DBA in the healthcare realm. He has supported several critical systems utilizing SQL Server and managed dozens of 24/7/365 SQL Server implementations. Following several years as a consultant, Matt is now the Director of Data and Infrastructure for rev.io, where he is implementing data governance, DevOps, and performance improvements enterprise-wide.

Ida Bergum is a Microsoft Data Platform MVP, and is currently working for Avanade Norway as a Solution Architect for the Data & AI Market Unit as well as leading Avanade's Community of Practice for Power BI globally. Ida has been advising on, architecting, and implementing modern data platform and BI solutions on Azure since she started at Avanade in 2015. She aims at advising and delivering great analytics experiences and data smart solutions for clients while sharing those experiences with the community. Her spare time is spent contributing to Data Platform User Group Norway among others, posting to her Twitter account, and cross-country skiing whenever she gets the opportunity.

Mia Chang works as a Solutions Architect specializing in machine learning for a tech company in Berlin, Germany. She cooperates with the customers on their development projects and delivers architecture leveraging services on the cloud. Her machine learning journey started with her studies in the field of applied mathematics, and computer science focused on algorithm research of strategic board games. During her seven-year professional journey, she has worked as a data scientist, and she has been proficient in the life cycle of ML projects. Apart from the work, Mia is passionate about open source projects and has been awarded the Microsoft AI MVP from 2017 to 2020. Her first book Microsoft AI MVP Book was published in 2019. She also dedicates her time to organizing communities and speaks at meetups and conferences. In addition to tech-related hobbies, she loves gardening, hiking, and traveling.

Ginger Grant is a consultant who shares what she has learned while working with data technology clients by providing training to people around the world. As a Microsoft MVP in Data Platform and a Microsoft Certified Trainer, she is proficient in creating solutions using Power BI and the Microsoft Azure Data Stack components, including Databricks, Data Factory, Data Lakes, Data Analytics, Synapse, and Machine Learning. Ginger co-authored Exam Ref 70-774 Perform Cloud Data Science with Azure Machine Learning and has a number of current exam certifications. When not working, she maintains her blog and spends time on twitter.

Bibliographic Information

Buying options

eBook
USD 54.99
Price excludes VAT (USA)
  • ISBN: 978-1-4842-7176-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD 69.99
Price excludes VAT (USA)