Beginning Azure Cognitive Services: Data-Driven Decision Making Through Artificial Intelligence - Couverture souple

Moniz, Alicia; Gordon, Matt; Bergum, Ida; Chang, Mia; Grant, Ginger

Couverture souple

ISBN 10 : 1484271750 ISBN 13 : 9781484271759

Editeur : Apress, 2021

Synopsis

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.

What You Will Learn

• 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

Who This Book Is For
Technical professionals who are interested in implementing artificial intelligence (AI) in pre-existing apps, expanding their value and skill sets, or learning more about AI for personal projects; for programmers working in languages such as C# and Python; and for those using low- and no-code platforms such as Microsoft Power Platform

A propos du livre

À propos de l'auteur

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 toher 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.

Détails de l'édition

• Éditeur: Apress
• Date d'édition: 2021
• Langue: anglais
• ISBN 10: 1484271750
• ISBN 13: 9781484271759
• Reliure: Broché
• Numéro d'édition: 1
• Nombre de pages: 328
• Coordonnées du fabricant: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Allemagne